WO2023232108A1 - 诊断及鉴别诊断非阿尔兹海默病认知障碍的方法、系统、组合物和试剂盒 - Google Patents

诊断及鉴别诊断非阿尔兹海默病认知障碍的方法、系统、组合物和试剂盒 Download PDF

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WO2023232108A1
WO2023232108A1 PCT/CN2023/097777 CN2023097777W WO2023232108A1 WO 2023232108 A1 WO2023232108 A1 WO 2023232108A1 CN 2023097777 W CN2023097777 W CN 2023097777W WO 2023232108 A1 WO2023232108 A1 WO 2023232108A1
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evs
cognitive impairment
markers
derived
central nervous
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PCT/CN2023/097777
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French (fr)
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章京
田辰
郭浈
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浙江大学医学院附属第一医院
浙江大学
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/02—Investigating particle size or size distribution
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids

Definitions

  • the present application relates to the field of biomedical technology, in particular to the field of in vitro diagnostic detection technology, and to methods and systems for detecting non-Alzheimer's disease cognitive impairment using dual markers and/or multiple markers, preferably using dual markers and/or multiple markers. /or methods and systems for simultaneous detection of non-Alzheimer's disease cognitive impairment using multiple markers.
  • AD Alzheimer’s Disease
  • ⁇ -amyloid deposition and neural tangles leading to neuronal damage in the central nervous system, and patients develop symptoms of cognitive impairment.
  • patients present with symptoms of cognitive impairment.
  • Cognitive impairment symptoms are not caused by AD alone.
  • non-AD cognitive disorders include Lewy body dementia, frontotemporal dementia, Pick's disease, amyotrophic lateral sclerosis with dementia and other diseases.
  • Diagnosis based on clinical cognitive scales and symptoms is difficult to distinguish AD from non-AD cognitive impairment. Imaging examinations are extremely expensive, but their role in identifying AD and non-AD cognitive impairment is limited. Differentiating AD from non-AD cognitive impairment It has always been a difficulty and research bottleneck in clinical work and scientific research. It has also caused great obstacles to patient diagnosis and treatment and subsequent treatment, affecting its therapeutic effect.
  • the diagnostic and differential diagnosis methods for non-AD cognitive impairment provided by this application can effectively improve the ability to differentiate between AD and non-AD cognitive impairment, assist in the diagnosis of non-AD cognitive impairment, and can greatly improve the misdiagnosis rate of non-AD cognitive impairment.
  • Biomarker detection based on cerebrospinal fluid is widely used in the research of neurological diseases.
  • This application is mainly based on peripheral blood testing to diagnose non-AD cognitive impairment, and can be widely used in clinical practice and large-scale screening.
  • the key biomarkers in this application are the innovatively discovered biomarkers related to peripheral blood nerve-derived extracellular vesicles (EVs), which can directly detect nervous system-derived EVs and the disease-related proteins they carry in peripheral blood. It directly reflects the lesions of the central nervous system, thereby realizing the diagnosis and differential diagnosis of non-AD cognitive disorders.
  • EVs peripheral blood nerve-derived extracellular vesicles
  • the core detection technology of this application is nano-flow detection technology. Through this technology, highly sensitive and high-throughput detection of EVs derived from the nervous system in peripheral blood can be achieved, and rapid and low-cost detection can be achieved, which is suitable for clinical applications and large-scale screening. Technical support provided.
  • This application focuses on the clinical and scientific research problem of diagnosis and differential diagnosis of non-AD cognitive impairment.
  • nanoflow detection technology Through new nanoflow detection technology and the innovative discovery of EV markers derived from the central nervous system, it can achieve rapid and efficient diagnosis and treatment of non-AD cognitive impairment.
  • Differential diagnosis provides new technical means and methods for clinical diagnosis of non-AD cognitive impairment.
  • this application utilizes biomarkers derived from the central nervous system to be identified in peripheral body fluids for diagnosis and differential diagnosis of non-AD cognitive impairment.
  • this application relates to the following:
  • a system for diagnosis and differential diagnosis of non-AD cognitive impairment which includes:
  • the first detection module is used to detect central nervous system-derived biomarkers of EVs in the body fluid of the subject to confirm the number and particle size of EVs carrying central nervous system-derived specific markers;
  • the second detection module is used to detect non-AD cognitive impairment-related markers of EVs in the subject's body fluid to confirm the number and particle size of EVs carrying non-AD cognitive impairment-related markers;
  • a diagnostic module that diagnoses whether the subject suffers from non-AD cognitive impairment based on the detection results of markers derived from the central nervous system and markers related to non-AD cognitive impairment obtained by the first detection module and the second detection module respectively.
  • the first detection module and the second detection module simultaneously detect central nervous system-derived markers in the subject's body fluid and detect non-AD cognitive impairment-related markers in the subject's body fluid;
  • the first detection module and the second detection module are the same module, which simultaneously detect central nervous system-derived markers in the subject's body fluid and detect non-AD cognitive impairment-related biomarkers in the subject's body fluid.
  • An enrichment module which is used to obtain the subject's body fluid and preprocess it to enrich EVs in the body fluid.
  • the enrichment module further includes a method for screening enriched EVs.
  • the diagnostic module counts the number of EVs that are simultaneously detected to carry biomarkers derived from the central nervous system and biomarkers related to non-AD cognitive impairment. Based on statistics, the number of EVs carrying biomarkers derived from the central nervous system and related to non-AD cognitive impairment are simultaneously detected. The ratio of the number of EVs of the marker to the number of total EVs is used to diagnose whether the subject suffers from non-AD cognitive impairment.
  • the particle size is the particle size corresponding to the location where the largest number of related protein-positive EVs are distributed, and the diagnostic module identifies and diagnoses the disease based on the detected particle size. Impaired subjects suffered from non-AD cognitive impairment rather than Alzheimer's disease subjects.
  • EVs are neuron-derived EVs, astrocyte-derived EVs, oligodendrocyte-derived EVs, or microglia.
  • Source EV EV
  • body fluid is selected from one or more of blood, serum, plasma, saliva, urine, lymph, semen or milk.
  • the central nervous system-derived marker is G Protein-Coupled Receptor 162 (GPR162), ⁇ -aminobutyric acid Gamma-Aminobutyric Acid Type A Receptor Subunit Delta (GABRD), acetylcholine transferase (Choline O-acetyltransferase, CHAT), glutamate ionotropic receptor NMDA type subunit 2D (Glutamate ionotropic receptor NMDA One or more of type subunit 2D, NR2D).
  • GPR162 G Protein-Coupled Receptor 162
  • GBRD Gamma-Aminobutyric Acid Type A Receptor Subunit Delta
  • acetylcholine transferase Choline O-acetyltransferase, CHAT
  • glutamate ionotropic receptor NMDA type subunit 2D glutamate ionotropic receptor NMDA One or more of type subunit 2D, NR2D.
  • non-AD cognitive impairment-related marker is phosphorylated tau at position 217 (pTau217) protein.
  • the enrichment module has sub-modules that perform one or more of the following steps: centrifugation, ultracentrifugation, ultrafiltration tube filtration, polymerization sedimentation, specific Antibody capture.
  • the first detection module is used to react EVs of the subject with labeled antibodies that specifically react with markers derived from the central nervous system, and The intensity of the labeling signal after the reaction is detected to determine the presence and content of EVs with biomarkers derived from the central nervous system.
  • the second detection module is used to perform a test on the subject's EVs with labeled antibodies that specifically react with non-AD cognitive impairment-related markers. reaction, and detecting the intensity of the labeling signal after the reaction to determine the presence and content of EVs with markers related to non-AD cognitive impairment.
  • label is selected from one or more than two of the following: fluorescent label, isotope label, enzyme label, chemiluminescent agent label, quantum dot label or colloidal gold label .
  • a composition for diagnosing and differentially diagnosing non-AD cognitive impairment comprising:
  • Antibodies targeting markers associated with non-AD cognitive impairment targeting markers associated with non-AD cognitive impairment.
  • composition according to item 15, wherein the central nervous system-derived marker is G protein-coupled receptor 162 (GPR162), gamma-aminobutyric acid type A receptor subtype Gamma-Aminobutyric Acid Type A Receptor Subunit Delta, GABRD, Choline O-acetyltransferase, CHAT, Glutamate ionotropic receptor NMDA type subunit 2D, NR2D ) one or more than two.
  • GPR162 G protein-coupled receptor 162
  • GABRD gamma-aminobutyric acid type A receptor subtype
  • Gamma-Aminobutyric Acid Type A Receptor Subunit Delta GABRD
  • Choline O-acetyltransferase CHAT
  • Glutamate ionotropic receptor NMDA type subunit 2D NR2D
  • composition according to item 15 or 16 wherein the non-AD cognitive impairment-related marker is phosphorylated tau at position 217 (pTau217) protein.
  • the antibody is a labeled antibody, and preferably the label is selected from one or more than two of the following: fluorescent labeling, isotope labeling, enzyme labeling, chemiluminescent labeling, quantum dot labeling, or colloidal gold labeling.
  • a kit for detecting non-AD cognitive impairment in a subject comprising:
  • Reagents for detecting markers of central nervous system origin of EV in biological fluids of subjects and
  • Reagents for detecting non-AD cognitive impairment-related markers of EV in biological fluids of subjects Reagents for detecting non-AD cognitive impairment-related markers of EV in biological fluids of subjects.
  • kits according to item 19 wherein the reagent for detecting a central nervous system-derived marker of EV in a subject's biological fluid and a non-AD cognition for detecting EV in the subject's biological fluid
  • the reagent for a disorder-related marker is the composition described in any one of items 15 to 18.
  • kit according to item 19 further comprising:
  • Reagents and devices for obtaining biological samples from a subject preferably reagents and devices for obtaining EVs from a subject.
  • a method for diagnosing and differentially diagnosing non-AD cognitive impairment which includes:
  • the first detection step is to detect central nervous system-derived biomarkers of EVs in the body fluid of the subject to confirm the number and particle size of EVs carrying central nervous system-derived specific markers;
  • the second detection step is to detect non-AD cognitive impairment-related markers of EVs in the subject's body fluid to confirm the number and particle size of EVs carrying non-AD cognitive impairment-related markers;
  • the diagnostic step is to diagnose whether the subject suffers from non-AD cognitive impairment based on the detection results of markers derived from the central nervous system and markers related to non-AD cognitive impairment obtained in the first detection step and the second detection step respectively.
  • the first detection step and the second detection step simultaneously detect central nervous system-derived markers in the subject's body fluid and detect non-AD cognitive impairment-related markers in the subject's body fluid;
  • the first detection step and the second detection step are the same step, which simultaneously detect central nervous system-derived markers in the subject's body fluid and detect non-AD cognitive impairment-related biomarkers in the subject's body fluid.
  • An enrichment step which obtains the subject's body fluid and preprocesses it to enrich the EVs in the body fluid.
  • the diagnostic step counts the number of EVs that are simultaneously detected to carry biomarkers derived from the central nervous system and biomarkers related to non-AD cognitive impairment. Based on statistics, the number of EVs carrying biomarkers derived from the central nervous system and related to non-AD cognitive impairment are simultaneously detected. The number of marker EVs accounts for the total EV The ratio of the number is used to diagnose whether the subject suffers from non-AD cognitive impairment.
  • EVs are neuron-derived EVs, astrocyte-derived EVs, oligodendrocyte-derived EVs, or microglia.
  • Source EV EV
  • the central nervous system-derived marker is G protein-coupled receptor 162 (G Protein-Coupled Receptor 162, GPR162), ⁇ -aminobutyric acid Gamma-Aminobutyric Acid Type A Receptor Subunit Delta (GABRD), acetylcholine transferase (Choline O-acetyltransferase, CHAT), glutamate ionotropic receptor NMDA type subunit 2D (Glutamate ionotropic receptor NMDA One or more of type subunit 2D, NR2D).
  • G protein-coupled receptor 162 G Protein-Coupled Receptor 162, GPR162
  • GBRD Gamma-Aminobutyric Acid Type A Receptor Subunit Delta
  • acetylcholine transferase Choline O-acetyltransferase, CHAT
  • glutamate ionotropic receptor NMDA type subunit 2D glutamate ionotropic receptor NMDA One or
  • the enrichment step has a sub-step of performing one or more of the following steps: centrifugation, ultracentrifugation, ultrafiltration tube filtration, polymerization sedimentation, and specific antibody capture. .
  • the label is selected from one or more than two of the following: fluorescent label, isotope label, enzyme label, chemiluminescent agent label, quantum dot label or colloidal gold markers.
  • Utilizing the methods, systems, kits and compositions of the present application can effectively enrich and specifically label biomarkers that can reflect changes in non-AD cognitive impairment diseases from peripheral body fluids. Compared with directly detecting diseases in peripheral body fluids, Relevant markers provide better diagnostic results.
  • the methods, systems, kits and compositions of the present application can effectively utilize peripheral body fluids for detection, thereby avoiding the traumatic acquisition of the cerebrospinal fluid of subjects, greatly reducing the sampling risks of subjects and greatly alleviating the difficulties of detection. degree, greatly increasing the clinical applicability and popularization of the test.
  • markers derived from the central nervous system and disease-related markers can be detected simultaneously, reducing sample detection time and making it more efficient and convenient.
  • the core of this application is a method and system for detecting non-AD cognitive impairment using dual markers and/or multiple markers, which can achieve simultaneous detection of dual markers and/or multiple markers, that is, using markers to confirm the presence of EVs.
  • disease-related markers are used to produce common detection results that serve for disease diagnosis, differential diagnosis, tracking and drug evaluation.
  • Figure 1A shows the quality control results of using 250nm fluorescent quality control spheres for a single-particle nanoflow cytometer
  • Figure 1B shows the quality control results of a single-particle nanoflow cytometer using quality control balls with a particle size of 68 to 155 nm;
  • Figure 1C shows the particle size distribution and concentration analysis results of EVs obtained by ultracentrifugation
  • Figure 2A shows that in the discovery cohort of Example 4, compared with the NC group and the NAD group, the ratio of GPR162 protein-positive EVs to the total EV number in the plasma of the AD group has a downward trend, but this difference is not statistically significant;
  • Figure 2B shows that in the discovery cohort of Example 4, compared with the NC group, pTau217 in the plasma of the AD group The ratio of protein-positive EVs to the total EV number was significantly reduced (****, p ⁇ 0.0001); compared with the NC group, the ratio of pTau217 protein-positive EVs to the total EV number in the plasma of the NAD group was also significantly lower (***, p ⁇ 0.001);
  • Figure 2C shows that in the discovery cohort of Example 4, the ratio of GPR162 protein and pTau217 protein double-positive EVs to the total number of EVs in plasma was in the NC group VS AD group (****, p ⁇ 0.0001), NC group VS NAD group ( ***,p ⁇ 0.001) there are significant differences;
  • Figure 2D shows that in the discovery cohort of Example 4, the diagnostic efficiency was evaluated through receiver operating characteristic curve (ROC) analysis.
  • the area under the curve (AUC) of the double-labeled GPR162 protein and pTau217 protein was: 0.85(NC VS AD);
  • Figure 2E shows that in the discovery cohort of Example 4, compared with the NC group and the NAD group, the ratio of GABRD protein-positive EVs to the total EV number in the plasma of the AD group has a downward trend, but this difference is not statistically significant;
  • Figure 2F shows that in the discovery cohort of Example 4, compared with the NC group, the ratio of pTau217 protein-positive EVs to the total number of EVs in the plasma of the AD group was significantly lower (*, p ⁇ 0.01);
  • Figure 2G shows that in the discovery cohort of Example 4, the ratio of GABRD protein and pTau217 protein double-positive EVs in plasma to the total number of EVs was in the NC group VS AD group (****, p ⁇ 0.0001), NC group VS NAD group ( ***,p ⁇ 0.001) there are significant differences;
  • Figure 2H shows that in the discovery cohort of Example 4, the diagnostic efficiency was evaluated through ROC analysis, and the AUC of GABRD protein and pTau217 protein double labeling was 0.85 (NC VS AD);
  • Figure 2I shows that in the discovery cohort of Example 4, the Enter method of logistic regression analysis was used to include GPR162+pTau217 and GABRD+pTau217 data, and the AUC was 0.91 (NC VS AD);
  • Figure 3A shows that in the discovery cohort of Example 4, compared with the NAD group, the particle size corresponding to the extreme value of the double-positive EV distribution of GPR162 protein and pTau217 protein in the plasma of the AD group was significantly reduced (***, p ⁇ 0.001);
  • Figure 3B shows that in the discovery cohort of Example 4, the particle size corresponding to the extreme value of the double-positive EV distribution of GABRD protein and pTau217 protein in the plasma of the AD group was also significantly reduced (**, p ⁇ 0.01);
  • Figure 3C shows that in the discovery cohort of Example 4, logistic regression analysis Enter method was used to include GPR162+pTau217 and GABRD+pTau217 distribution extreme particle size data, and the AUC was 0.82 (AD VS NAD);
  • Figure 4A shows that in the validation cohort of Example 4, compared with the NC group and the NAD group, the ratio of GPR162 protein-positive EVs to the total EV number in the plasma of the AD group has a downward trend, but this difference is not statistically significant;
  • Figure 4B shows that in the validation cohort of Example 4, compared with the NC group, the ratio of pTau217 protein-positive EVs to the total number of EVs in the plasma of the AD group was significantly reduced (****, p ⁇ 0.0001); compared with the NAD group, The ratio of pTau217 protein-positive EVs to the total number of EVs in the plasma of the AD group was also significantly reduced (****, p ⁇ 0.0001);
  • Figure 4C shows that in the validation cohort of Example 4, the ratio of GPR162 protein and pTau217 protein double-positive EVs in plasma to the total number of EVs was in the NC group VS AD group (****, p ⁇ 0.0001), AD group VS NAD group ( ****,p ⁇ 0.0001) there are significant differences;
  • Figure 4D shows that in the validation cohort of Example 4, the diagnostic efficiency was evaluated through ROC analysis.
  • the AUC of the double labeling of GPR162 protein and pTau217 protein was 0.74 (NC VS AD);
  • Figure 4E shows that in the validation cohort of Example 4, compared with the NC group, the ratio of GABRD protein-positive EVs to the total number of EVs in the plasma of the AD group significantly decreased (***, p ⁇ 0.001); compared with the NC group, the ratio of NAD The ratio of GABRD protein-positive EVs to total EVs in the plasma of the NAD group also decreased significantly (****, p ⁇ 0.0001); in addition, compared with the AD group, the ratio of GABRD protein-positive EVs to the total EVs in the plasma of the NAD group was significantly lower (****, p ⁇ 0.0001). Decline (****,p ⁇ 0.0001);
  • Figure 4F shows that in the validation cohort of Example 4, compared with the NC group, the ratio of pTau217 protein-positive EVs to the total number of EVs in the plasma of the AD group was significantly lower (***, p ⁇ 0.001); the ratio of pTau217 protein-positive EVs in the plasma of the NAD group was significantly lower The ratio of EV to total EV number was also significantly reduced (***, p ⁇ 0.001);
  • Figure 4G shows that in the validation cohort of Example 4, the ratio of GABRD protein and pTau217 protein double-positive EVs to the total number of EVs in plasma was in the NC group VS AD group (****, p ⁇ 0.0001), NC group VS NAD group ( ****, p ⁇ 0.0001), AD group VS NAD group (*, p ⁇ 0.01), there are significant differences;
  • Figure 4H shows that in the validation cohort of Example 4, the diagnostic efficiency was evaluated through ROC analysis, and the double-labeled AUC of GABRD protein and pTau217 protein was 0.84 (NC VS AD);
  • Figure 4I shows that in the validation cohort of Example 4, using the Enter method of logistic regression analysis to include GPR162+pTau217 and GABRD+pTau217 data, the AUC was 0.93 (NC VS AD).
  • Figure 5A shows that in the validation cohort of Example 4, compared with the NAD group, the particle size corresponding to the extreme value of the double-positive EV distribution of GPR162 protein and pTau217 protein in the plasma of the AD group was significantly reduced (***, p ⁇ 0.001);
  • Figure 5B shows that in the validation cohort of Example 4, the particle size corresponding to the extreme value of the double-positive EV distribution of GABRD protein and pTau217 protein in the plasma of the AD group was also significantly reduced (**, p ⁇ 0.01);
  • Figure 5C shows that in the validation cohort of Example 4, the enter method of logistic regression analysis was used to include GPR162+pTau217 and GABRD+pTau217 distribution extreme particle size data, and the AUC was 0.88 (AD VS NAD);
  • Figure 6A shows that in Example 7, compared with the NC group and the NAD group, the ratio of CHAT protein-positive EVs to the total number of EVs in the plasma of the AD group was significantly reduced (**, p ⁇ 0.01);
  • Figure 6B shows that in Example 7, compared with the NC group, the ratio of pTau217 protein-positive EVs to the total number of EVs in the plasma of the AD group was significantly reduced (****, p ⁇ 0.001); compared with the NC group, the ratio of the plasma of the NAD group The ratio of pTau217 protein-positive EVs to the total EV number was also significantly reduced (***, p ⁇ 0.01);
  • Figure 6C shows that in Example 7, the ratio of double-positive EVs for CHAT protein and pTau217 protein in plasma to the total number of EVs was different between NC group VS AD group (****, p ⁇ 0.001), NC group VS NAD group (*** ,p ⁇ 0.05), there are significant differences;
  • Figure 6D shows that in Example 7, the diagnostic efficiency was evaluated through ROC analysis, and the AUC of CHAT protein and pTau217 protein double labeling was 0.88 (NC VS AD);
  • Figure 6E shows that in Example 7, the diagnostic efficiency was evaluated by ROC analysis, and the AUC of CHAT protein and pTau217 protein double labeling was 0.88 (AD VS NAD);
  • Figure 6F shows that in Example 7, compared with the NC group, the proportion of NR2D protein-positive EVs in the total EV number in the plasma of the AD group was significantly reduced (***, p ⁇ 0.001); compared with the NAD group, the proportion of NR2D protein-positive EVs in the plasma of the AD group The proportion of NR2D protein-positive EVs in the total EV number was also significantly reduced (***, p ⁇ 0.001);
  • Figure 6G shows that in Example 7, compared with the NC group, the ratio of pTau217 protein-positive EVs to the total number of EVs in the plasma of the AD group was significantly reduced (****, p ⁇ 0.0001); compared with the NAD group, the ratio of the plasma of the AD group The proportion of pTau217 protein-positive EVs in the total EV number was also significantly reduced (***, p ⁇ 0.001);
  • Figure 6H shows that in Example 7, the proportion of double-positive EVs for NR2D protein and pTau217 protein in the plasma to the total number of EVs was different between NC group VS AD group (****, p ⁇ 0.0001), NC group VS NAD group (*** ,p ⁇ 0.001), there are significant differences;
  • Figure 6I shows that in Example 7, the diagnostic efficiency was evaluated by ROC analysis, and the AUC of the double labeling of NR2D protein and pTau217 protein was 0.82 (NC VS AD);
  • Figure 6J shows that in the discovery cohort of Example 7, the diagnostic efficiency was evaluated through ROC analysis.
  • the AUC of the double labeling of NR2D protein and pTau217 protein was 0.69 (AD VS NAD);
  • Extracellular Vesicles are mature mediators of intercellular communication. They are small membrane vesicles released by different types of activated or apoptotic cells, including white blood cells, platelets, red blood cells and endothelial cells. It can be detected in human and animal body fluids. EVs are divided into three main groups: apoptotic bodies, microvesicles and exosomes.
  • the present application relates to a method, system, composition and kit for diagnosing and differentially diagnosing non-Alzheimer's disease cognitive impairment, that is, "non-AD cognitive impairment", which includes : Detect central nervous system-derived markers of EV in subjects’ biological fluids, detect non-AD cognitive impairment-related markers of EV in subjects’ biological fluids, and detect markers based on central nervous system The test results of system-derived markers and markers related to non-AD cognitive impairment are used to identify and diagnose whether subjects suffer from non-AD cognitive impairment.
  • the present application relates to a method, system, composition and kit for diagnosing and differentially diagnosing non-Alzheimer's disease cognitive impairment, that is, "non-AD cognitive impairment", which includes : Detect central nervous system-derived markers of EVs in subjects’ biological fluids to confirm the number and particle size of EVs with central nervous system-derived markers, and detect non-AD cognitive impairment-related diseases carried by EVs in subjects’ biological fluids. Markers are used to confirm the number and particle size of EVs with markers related to non-AD cognitive impairment, and to identify whether subjects are diagnosed based on the detection results of markers derived from the central nervous system and markers related to non-AD cognitive impairment. Suffering from non-AD cognitive impairment, wherein the detection of markers derived from the central nervous system in the subject's biological fluid and the detection of markers related to non-AD cognitive impairment in the subject's biological fluid are performed simultaneously.
  • the present application relates to a method, system, composition and kit for diagnosing and differentially diagnosing non-Alzheimer's disease cognitive impairment, that is, "non-AD cognitive impairment", which includes :
  • the first detection module is used to detect central nervous system-derived markers carried by EVs in the subject's body fluid to confirm the number and particle size of EVs carrying central nervous system-derived markers
  • the second detection module is used to detect non-AD cognitive impairment-related markers carried by EVs in the subject's body fluid to confirm the number and particle size of EVs with non-AD cognitive impairment-related markers
  • a diagnostic module based on the first detection module and the second The detection module obtains the detection results of markers derived from the central nervous system and markers related to non-AD cognitive impairment to identify and diagnose whether the subject suffers from non-AD cognitive impairment.
  • the present application relates to a method, system, composition and kit for diagnosing and differentially diagnosing non-Alzheimer's disease cognitive impairment, that is, "non-AD cognitive impairment", which includes :
  • the first detection module is used to detect central nervous system-derived markers carried by EVs in the subject's body fluid to confirm the number and particle size of EVs carrying central nervous system-derived markers
  • the second detection module is used to detect non-AD cognitive impairment-related markers carried by EVs in the subject's body fluid to confirm the number and particle size of EVs carrying non-AD cognitive impairment-related markers
  • a diagnostic module based on the first detection module and the second The detection module obtains the detection results of markers derived from the central nervous system and markers related to non-AD cognitive impairment to identify and diagnose whether the subject suffers from non-AD cognitive impairment.
  • the first detection module and the second detection module simultaneously detect central nervous system-derived markers in the subject's biological fluid and detect the central nervous system-derived markers in the subject's biological fluid.
  • Markers related to non-AD cognitive impairment; or the first detection module and the second detection module are the same module, which simultaneously detects central nervous system-derived markers in the subject's biological fluid and detects the subject's biological fluid.
  • Non-AD cognitive impairment-related markers in body fluids are the same module, which simultaneously detects central nervous system-derived markers in the subject's biological fluid and detects the subject's biological fluid.
  • the inventor has creatively developed a new method and system, that is, using dual markers and/or multiple markers with different functions for detection, especially At the same time, through detection of such dual markers and/or multiple markers, non-AD cognitive impairment can be effectively diagnosed and differentially diagnosed using only a small amount of peripheral body fluids.
  • detection methods and systems do not require the extraction of the patient's cerebrospinal fluid, which greatly reduces the patient's sampling risk.
  • the accuracy of the detection can be greatly improved. If further simultaneous detection is performed, the overall detection efficiency can also be improved. .
  • the method of the present application also includes: obtaining the subject's biological fluid and preprocessing it to enrich EVs in the biological fluid.
  • Detecting central nervous system-derived markers in the subject's biological fluid means detecting the subject's biological fluid.
  • Central nervous system-derived markers in EVs enriched in the subject's body fluid, and detecting non-AD cognitive impairment-related markers in the subject's body fluid refers to detecting non-AD markers carried by EVs enriched in the subject's body fluid. Markers associated with cognitive impairment.
  • the method of the present application also includes: obtaining the biological fluid of the subject and preprocessing it to enrich the EVs in the biological fluid, screening the enriched EV, and detecting the central nervous system in the biological fluid of the subject.
  • System-derived markers refer to the detection of central nervous system-derived markers in EVs screened in the subject's body fluids
  • the detection of markers related to non-AD cognitive impairment in the subjects' body fluids refer to the detection of markers screened in the subject's body fluids.
  • EVs carry markers associated with non-AD cognitive impairment.
  • the method of the present application also includes a diagnostic module that counts the number of EVs that are simultaneously detected to carry central nervous system-derived markers and non-AD cognitive impairment-related markers, and based on statistics, the number of EVs that are simultaneously detected to be carrying central nervous system-derived markers and non-AD cognitive impairment-related markers.
  • the ratio of the number of EVs of markers related to cognitive impairment to the number of total EVs is used to identify and diagnose whether subjects suffer from non-AD cognitive impairment.
  • the ratio of the number of EVs carrying markers derived from the central nervous system and markers related to cognitive impairment that are simultaneously detected to the number of total EV biological samples values there were significant differences between healthy subjects and cognitively impaired (AD and non-AD) subjects. For example, this ratio is significantly lower in AD and non-AD subjects compared with healthy subjects.
  • the diagnostic module distinguishes whether the subject suffering from cognitive impairment suffers from Alzheimer's disease or non-AD cognitive impairment based on the detected particle size, where the particle size is the particle size corresponding to the extreme value of the distribution.
  • the particle size corresponding to the distribution extreme value refers to the particle size with the largest number of distributed particles.
  • the particle size corresponding to the distribution extreme value is measured by a nanoflow detector and a related nanoparticle flow analyzer.
  • whether the subject suffers from cognitive impairment can be determined by the ratio of the number of EVs of markers derived from the central nervous system and non-AD-related markers to the number of total EVs.
  • the distinction between Alzheimer's disease and non-AD cognitive impairment in cognitive impairment needs to be further based on the distribution of detected central nervous system-derived markers of EVs and markers related to non-AD cognitive impairment of EVs. value corresponds to the particle size.
  • the particle size corresponding to the extreme value of the distribution carrying markers derived from the central nervous system and markers related to cognitive impairment was simultaneously detected in AD and non-AD cognitive impairment subjects. There are significant differences. For example, this particle size is significantly reduced in AD subjects compared to non-AD subjects.
  • system of the present application also includes: an enrichment module, which pre-processes the biological fluid obtained from the subject to enrich EVs in the biological fluid.
  • the enrichment module may also include screening the enriched EVs to further improve the accuracy of the obtained EVs.
  • the present application also relates to a composition for detecting non-AD cognitive impairment, which includes: an antibody for targeting markers derived from the central nervous system, and an antibody for targeting markers related to non-AD cognitive impairment. .
  • the present application also relates to a kit for detecting non-AD cognitive impairment in a subject, which includes: a reagent for detecting central nervous system-derived markers of EV in the biological fluid of the subject; Reagents for non-AD cognitive impairment-related markers of EVs in human body fluids.
  • a reagent for detecting a central nervous system-derived marker in a subject's biological fluid and a reagent for detecting a non-AD cognitive impairment-related marker in the subject's biological fluid is the above composition described in this application.
  • the biological fluid is blood, serum, plasma, saliva, urine, lymph, semen or milk.
  • Preferred biological fluids are blood, serum, plasma, saliva or urine.
  • the method used to obtain the subject's biological fluids can be any method known to those skilled in the art. Those skilled in the art can obtain the biological fluid from the subject using a method specific to the selected biological fluid.
  • Extracellular vesicles refer to vesicle-like bodies with a double-layer membrane structure that are shed from the cell membrane or secreted from the cells, with diameters ranging from 40nm to 1000nm.
  • EVs are mainly composed of microvesicles (MVs) and exosomes (Exosomes, Exs).
  • MVs microvesicles
  • Exs Exosomes
  • Microvesicles are small vesicles that are shed from the cell membrane after cell activation, injury or apoptosis, with a diameter of approximately 100nm to 1000nm. Exosomes are released outside the cells in the form of exosomes after the fusion of intracellular multivesicular bodies with the cell membrane.
  • EVs have a diameter of about 30 to 150 nm and can be released by many different types of cells, and Performs diverse cellular functions including intercellular communication, antigen presentation, and transfer of proteins and nucleic acids.
  • EVs widely exist in cell culture supernatants and various body fluids (blood, lymph, saliva, urine, semen, milk), carrying a variety of proteins, lipids, DNA, mRNA, miRNA, etc. related to cell origin. Processes such as intercellular communication, cell migration, angiogenesis, and immune regulation.
  • the EVs are neuron-derived EVs, astrocyte-derived EVs, oligodendrocyte-derived EVs or microglia-derived EVs.
  • the method of obtaining the subject's biological fluid and preprocessing it to enrich EVs in the biological fluid may be centrifugation, ultracentrifugation, ultrasonic Filter tube filtration, polymeric sedimentation, or specific antibody capture.
  • centrifugation, ultracentrifugation, ultrafiltration tube filtration, polymerization sedimentation or specific antibody capture all have meanings that can be understood by those skilled in the art, and those skilled in the art can select an appropriate method according to the EVs to be obtained.
  • an ultracentrifugation method is used to enrich EVs from biological fluids, especially to enrich EVs derived from neurons, EVs derived from astrocytes, and oligodendrocytes.
  • ordinary centrifugation or ultrafiltration tube filtration is used to enrich EVs, especially to enrich EVs derived from neurons, EVs derived from astrocytes, and oligodendrocytes. derived EVs or microglia-derived EVs.
  • lipid probes are used to enrich EVs, especially EVs derived from neurons, EVs derived from astrocytes, and EVs derived from oligodendrocytes. or microglia-derived EVs for screening.
  • the sequence of the lipid probe is TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT (SEQ ID NO: 1); 5' end modification: 5'6-CY3; 3' end modification: 3'Cholesteryl.
  • the central nervous system-derived marker is a biomarker derived from the following neurons or cells: mature neurons, oligodendrocytes, Astrocytes, microglia, immature neurons, Schwann cells, radial glia, intermediate precursor cells, glutamatergic neurons, GABAergic neurons, dopaminergic neurons, 5-hydroxytryptamine Neurons, cholinergic neurons.
  • the central nervous system-derived marker is a neuron-derived biomarker.
  • the central nervous system-derived marker is an astrocyte- and/or oligodendrocyte-derived biomarker.
  • the central nervous system-derived marker is a marker located on the surface of central nervous system-derived EVs.
  • the marker derived from the central nervous system is G protein-coupled receptor 162 (G Protein-Coupled Receptor 162, GPR162), ⁇ -aminobutyrate Gamma-Aminobutyric Acid Type A Receptor Subunit Delta (GABRD), Gamma-Aminobutyric Acid Type A Receptor Subunit Delta (GABRD), acetylcholine transfer One or more of enzyme (Choline O-acetyltransferase, CHAT), glutamate ionotropic receptor NMDA type subunit 2D (Glutamate ionotropic receptor NMDA type subunit 2D, NR2D).
  • G protein-coupled receptor 162 G Protein-Coupled Receptor 162, GPR162
  • GBRD Gamma-Aminobutyric Acid Type A Receptor Subunit Delta
  • GBRD Gamma-Aminobutyric Acid Type A Receptor Subunit Delta
  • acetylcholine transfer One or more of enzyme
  • the marker derived from the central nervous system is G protein-coupled receptor 162 (G Protein-Coupled Receptor 162, GPR162).
  • the central nervous system-derived marker is Gamma-Aminobutyric Acid Type A Receptor Subunit ⁇ (Gamma-Aminobutyric Acid Type A Receptor Subunit Delta, GABRD).
  • the markers derived from the central nervous system are G protein-coupled receptor 162 (G Protein-Coupled Receptor 162, GPR162) and ⁇ -aminobutyrate.
  • G protein-coupled receptor 162 G Protein-Coupled Receptor 162, GPR162
  • GBRD Gamma-Aminobutyric Acid Type A Receptor Subunit Delta
  • the marker derived from the central nervous system is acetylcholine transferase (Choline O-acetyltransferase, CHAT).
  • the marker derived from the central nervous system is glutamate ionotropic receptor NMDA type subunit 2D (Glutamate ionotropic receptor NMDA type subunit 2D, NR2D).
  • the central nervous system-derived markers are acetylcholine transferase (Choline O-acetyltransferase, CHAT) and glutamate ionotropic receptor NMDA type Subunit 2D (Glutamate ionotropic receptor NMDA type subunit 2D, NR2D).
  • the non-AD cognitive impairment-related marker is phosphorylated tau at position 217 (pTau217) protein.
  • the marker derived from the central nervous system is GPR162 protein
  • the marker related to non-AD cognitive impairment is pTau217 protein.
  • the marker derived from the central nervous system is GABRD protein
  • the marker related to non-AD cognitive impairment is pTau217 protein.
  • the markers derived from the central nervous system are GPR162 protein and GABRD protein, and the marker related to non-AD cognitive impairment is pTau217 protein.
  • the marker derived from the central nervous system is CHAT protein
  • the marker related to non-AD cognitive impairment is pTau217 protein.
  • the marker derived from the central nervous system is NR2D protein
  • the marker related to non-AD cognitive impairment is pTau217 protein.
  • the markers derived from the central nervous system are CHAT protein and NR2D protein, and the marker related to non-AD cognitive impairment is pTau217 protein.
  • the step of detecting central nervous system-derived markers in the biological fluid of the subject in a specific embodiment of the method or system or composition or kit of the present application, the step of detecting central nervous system-derived markers in the biological fluid of the subject
  • the steps include: reacting the subject's EVs with labeled antibodies that specifically react with markers derived from the central nervous system, and detecting the intensity of the labeled signal after the reaction to determine the presence of EVs carrying markers derived from the central nervous system. and content;
  • the non-AD cognitive impairment-related markers are proteins
  • the step of detecting the non-AD cognitive impairment-related markers in the biological fluid of the subject includes: making the subject's EVs and labeled Antibodies that specifically react with non-AD cognitive impairment-related markers are reacted, and the intensity of the labeling signal after the reaction is detected to determine the presence and content of EVs carrying non-AD cognitive impairment-related markers.
  • the subject's EV simultaneously reacts with a labeled antibody that specifically reacts with a marker derived from the central nervous system and a labeled antibody that specifically reacts with a marker related to non-AD cognitive impairment.
  • the reactive antibodies react to efficiently track double-labeled and/or multi-labeled positive EVs.
  • it also includes counting the number of EVs that detect both markers derived from the central nervous system and markers related to non-AD cognitive impairment, and Measure the particle size of EVs that detect both central nervous system-derived markers and non-AD cognitive impairment-related markers, so that after tracking double- and/or multi-label positive EVs, this can also be fully considered.
  • the label is selected from one or more than two of the following: fluorescent label, isotope label, enzyme label, chemiluminescent agent label, quantum dot markers or colloidal gold markers.
  • the fluorescent label is selected from one or more than two of the following: Qdot525, Qdot545, Qdot565, Qdot585, Qdot605, Qdot625, Qdot655, Qdot705, Qdot800, Alexa350, Alexa 405, Alexa488, Alexa 532, Alexa546, Alexa555, Alexa 568, Alexa 594, Alexa647, Alexa700, Alexa750.
  • isotope labeling enzyme labeling, chemiluminescent labeling, quantum dot labeling or colloidal gold labeling can all use methods well known to those skilled in the art.
  • the intensity of the labeling signal after the reaction can be detected to determine the presence and content of markers derived from the central nervous system, such as immunoassays, such as ELISA, Luminex, MSD, Quanterix, Singulex, eCL8000, Cobas are the preferred methods for measuring protein biomarkers.
  • immunoassays such as ELISA, Luminex, MSD, Quanterix, Singulex, eCL8000, Cobas are the preferred methods for measuring protein biomarkers.
  • the method or system or composition or kit of the present application is used to statistically detect the number of EVs carrying both markers derived from the central nervous system and markers related to non-AD cognitive impairment, and/ Or detection instruments that measure the particle size of EVs carrying both markers derived from the central nervous system and markers related to non-AD cognitive impairment, including but not limited to particle size analyzers and nanoflow cytometers.
  • particle size analyzers and nanoflow cytometers include particle size analyzers and nanoflow cytometers.
  • nanoparticle tracking technology is used to detect the particle size of EVs
  • nanoflow analysis technology is used to detect the number of double-positive EVs.
  • composition for detecting non-AD cognitive impairment which includes: an antibody for targeting markers derived from the central nervous system, and a composition for targeting non-AD cognitive impairment.
  • Antibodies against markers associated with known disorders include: an antibody for targeting markers derived from the central nervous system, and a composition for targeting non-AD cognitive impairment. Antibodies against markers associated with known disorders.
  • the antibody for targeting markers derived from the central nervous system and the antibody for targeting markers related to non-AD cognitive impairment are labeled antibodies, preferably
  • the label is selected from one or more of the following: fluorescent label, isotope label, enzyme label, chemiluminescent agent label, quantum dot label or colloidal gold label.
  • a composition for detecting non-AD cognitive impairment includes: an antibody for targeting GPR162 protein, and an antibody for targeting tau (pTau217) protein.
  • a composition for detecting non-AD cognitive impairment includes: an antibody for targeting GABRD protein, and an antibody for targeting tau (pTau217) protein.
  • the present application relates to a kit for detecting non-AD cognitive impairment in a subject, which includes: a reagent for detecting central nervous system-derived markers in the subject's biological fluid, and a reagent for detecting the subject's biological fluid.
  • Reagents for non-AD cognitive impairment-related markers of EV in body fluids. described for inspection The reagent for detecting central nervous system-derived markers of EV in the subject's biological fluid and the reagent for detecting markers related to non-AD cognitive impairment in the subject's biological fluid may be the above-mentioned compositions related to the present application.
  • kits involved in this application also include reagents and devices for obtaining EVs from a subject.
  • the reagents and devices used to obtain EVs may include commonly used kits and devices known to those skilled in the art.
  • Utilizing the methods, systems, kits and compositions of the present application can effectively enrich and specifically label biomarkers that can reflect changes in non-AD cognitive impairment from peripheral body fluids. Compared with directly detecting disease-related disease in peripheral body fluids, markers, the diagnostic effect is better.
  • the methods, systems, kits and compositions of the present application can effectively utilize peripheral body fluids for detection, thereby avoiding the traumatic acquisition of the cerebrospinal fluid of subjects, greatly reducing the sampling risks of subjects and greatly alleviating the difficulties of detection. degree, greatly increasing the clinical applicability and popularization of the test.
  • markers derived from the central nervous system and disease-related markers can be detected simultaneously, reducing sample detection time and making it more efficient and convenient.
  • Nanofcm was used to characterize the particle size and concentration of EVs obtained by ultracentrifugation.
  • Figure 1A shows the quality control results of a single-particle nanoflow cytometer using 250nm fluorescent quality control spheres.
  • the scattered light channel (SS), green fluorescence channel (FITC) and red fluorescence channel (PC5) are all in a state with high signal values (column 1) and uniform signal peaks (columns 2 and 3); indicating single-particle nanoflow
  • the detection of fluorescence signals by the cytometer has been adjusted to a better state.
  • Figure 1B shows the quality control results of a single-particle nanoflow cytometer using quality control spheres with a particle size of 68 to 155 nm.
  • the particle size quality control sphere is a mixture of four types of spheres with different particle sizes.
  • the single-particle nanoflow cytometer can accurately detect the particles of four different particle size groups in the particle size sphere. Description The instrument's detection of particle size signals has been adjusted to a better state.
  • Alexa Fluro fluorescent labeling kit was used to label antibodies to central nervous system-derived EV biomarkers and antibodies to related Alzheimer's disease biomarkers.
  • the antibodies for EV biomarkers derived from the central nervous system are GPR162 and GABRD polyclonal antibodies.
  • the antibody for Alzheimer's disease biomarker is pTau217 polyclonal antibody.
  • the reagent for labeling GPR162 and GABRD polyclonal antibodies is Zenon TM Alexa Fluor TM 488 Rabbit IgG Labeling Kit, which can be purchased from Thermo Fisher Scientific; the reagent for labeling pTau217 polyclonal antibody was Zenon TM Alexa Fluor TM 647 Rabbit IgG Labeling Kit, purchased from Thermo Fisher Scientific.
  • This experiment involves the central nervous system-specific markers GPR162 and GABRD; the disease-related marker antibody pTau217.
  • step (3) Add 3 ⁇ L (3 ⁇ g) Zenon TM Alexa Fluor TM Labeling Kit B solution to the solution in step (2) (dilute B solution to 1 ⁇ g/ ⁇ L), mix and incubate at room temperature (25°C) in the dark for 10 minutes to quench Kill free fluorescence;
  • NanoFCM nanoflow analyzer to detect label signal intensity and particle size distribution, from and determine the presence and content of relevant biomarkers.
  • Plasma samples were obtained from 28 age- and gender-matched healthy controls (NC group), 44 Alzheimer's disease subjects (AD group), and 31 non-AD-cognitive impairment (NAD group) as the discovery cohort. , conduct experiments using the method of Example 3 above.
  • Nanoflow cytometer NanoFCM uses the nanoflow cytometer NanoFCM to detect the number of EVs labeled with GPR162, GABRD single fluorescent label, pTau217 single fluorescent label, GPR162 and pTau217 double fluorescent label, and the number of EVs with GABRD and pTau217 dual fluorescent label, and calculate their ratio to the total number of EVs. , to test its ability to distinguish NC, AD, and NAD.
  • NC and AD patients can be well distinguished based on the ratio of GPR162+pTau217 or GABRD+pTau217 double-positive EVs to the total number of EVs, the ability to differentiate between AD and NAD is limited. Therefore, using particle size distribution as a reference factor, we explore the use of extreme particle size to distinguish AD and NAD; that is, in different experimental group samples, the particle size distribution of target protein-positive vesicles may be different; we use the target protein The particle size corresponding to the maximum number of positive vesicles was analyzed. The results are as follows:
  • the results of the discovery cohort showed that the ratio of GPR162 protein and pTau217 protein double-positive EVs to the total EV number in plasma and the ratio of GABRD protein and pTau217 protein double-positive EVs to the total EV number in plasma were both good at distinguishing healthy controls and Alzheimer's disease.
  • the potential of Heimer's disease especially the joint diagnosis of GPR162+pTau217 double-positive EV ratio and GABRD+pTau217 double-positive EV ratio. Joint analysis of the distribution extreme particle sizes of GPR162+pTau217 double-positive EVs and GABRD+pTau217 double-positive EVs can better differentiate and diagnose Alzheimer's disease and non-AD-dementia.
  • Plasma samples were obtained from 57 age- and gender-matched healthy controls (NC group), 88 Alzheimer's disease subjects (AD group), and 62 non-AD-dementia (NAD group) as a validation cohort. The experiment was carried out according to the method of Example 3 above.
  • the ratio of GABRD protein-positive EVs in the plasma of the AD group to the total EV number was significantly decreased (***, p ⁇ 0.001); compared with the NC group, the ratio of GABRD protein-positive EVs in the plasma of the NAD group The ratio of the number of GABRD protein-positive EVs to the total number of EVs in the plasma of the NAD group was also significantly decreased (****, p ⁇ 0.0001); in addition, compared with the AD group, the ratio of GABRD protein-positive EVs to the total number of EVs in the plasma of the NAD group was significantly decreased (****, p ⁇ 0.0001).
  • NC and AD patients can be well distinguished by the ratio of GPR162+pTau217 or GABRD+pTau217 double-positive EVs to the total number of EVs, the ability to differentiate between AD and NAD is limited. Therefore, we still use particle size distribution as a reference factor and use extreme particle sizes to distinguish AD and NAD; we analyze the particle size corresponding to the maximum number of target protein-positive vesicles, and the results are as follows:
  • the results of the validation cohort were consistent with the discovery cohort, that is, the ratio of GPR162 protein and pTau217 protein double-positive EVs to the total EV number in plasma, and the ratio of GABRD protein and pTau217 protein double-positive EVs to the total EV number in plasma were well differentiated.
  • Joint analysis of the distribution extreme particle sizes of GPR162+pTau217 double-positive EVs and GABRD+pTau217 double-positive EVs can better differentiate and diagnose Alzheimer's disease and non-AD-dementia.
  • Example 4 show that joint analysis using the ratio of GPR162+pTau217 double-positive EVs and the ratio of GABRD+pTau217 double-positive EVs can better distinguish between healthy controls and Alzheimer's disease. Joint analysis of the distribution extreme particle sizes of GPR162+pTau217 double-positive EVs and GABRD+pTau217 double-positive EVs can better differentiate and diagnose Alzheimer's disease and non-AD-dementia.
  • Alexa Fluro fluorescent labeling kit to label CHAT, NR2D, and pTau217 antibodies.
  • the reagent for labeling CHAT antibodies is Zenon TM Alexa Fluor TM 488 Mouse IgG2b Labeling Kit, purchased from Thermo Fisher Scientific;
  • the reagent for labeling NR2D antibodies is Zenon TM Alexa Fluor TM 488 Rabbit IgG Labeling Kit, purchased from Thermo Fisher Scientific;
  • the labeling pTau217 antibody The reagent used was Zenon TM Alexa Fluor TM 647 Rabbit IgG Labeling Kit, purchased from Thermo Fisher Scientific.
  • step (3) Add 3 ⁇ L (3 ⁇ g) Zenon TM Alexa Fluor TM Labeling Kit B solution to the solution in step (2) (dilute B solution to 1 ⁇ g/ ⁇ L), mix and incubate at room temperature (25°C) in the dark for 10 minutes to quench Kill unbound free fluorescein;
  • Reagents used synthetic DNA anchor, whose sequence is TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT (SEQ ID NO: 1); 5' end modification: 5 ⁇ 6-CY3; 3' end modification: 3 ⁇ Cholesteryl.
  • the lipid probe can bind to the EV membrane, and particles with positive probe labeling are considered to be real EVs; this method further improves the scientific nature and accuracy of EV labeling.
  • Plasma samples were obtained from 20 age- and gender-matched healthy controls (NC group), 20 Alzheimer's disease subjects (AD group), and 20 non-AD-dementia (NAD group), and used the above Example 6 method to conduct experiments.
  • NC group 20 age- and gender-matched healthy controls
  • AD group 20 Alzheimer's disease subjects
  • NAD group 20 non-AD-dementia
  • the ratio of pTau217 protein-positive EVs to total EVs in the plasma of the AD group was significantly lower (****, p ⁇ 0.0001); compared with the NAD group, the ratio of pTau217 protein-positive EVs to the total EVs in the plasma of the AD group The proportion of the number was also significantly reduced (***, p ⁇ 0.001) ( Figure 6G); the proportion of double-positive EVs for NR2D protein and pTau217 protein in plasma to the total number of EVs was significantly lower in the NC group VS AD group (****, p ⁇ 0.0001), NC group VS NAD group (***, p ⁇ 0.001), there were significant differences (Figure 6H). Diagnostic efficiency was evaluated through ROC analysis.
  • the AUCs of NR2D protein and pTau217 protein double labeling were 0.82 (NC vs AD) ( Figure 6I) and 0.69 (AD vs NAD) ( Figure 6J) respectively.

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Abstract

一种诊断及鉴别诊断非阿尔兹海默病（AD）认知障碍，即"非AD认知障碍"的方法、系统、组合物和试剂盒。其中，用于诊断"非AD认知障碍"的系统包括：第一检测模块，其用于检测受试者体液中细胞外囊泡（EV）的中枢神经系统来源生物标志物，以确认携带中枢神经系统来源特异性标志物的EV的数量和粒径；第二检测模块，其用于检测受试者体液中EV的非AD认知障碍相关的标志物以确认携带非AD认知障碍相关的标志物的EV的数量和粒径；以及诊断及鉴别诊断模块，其基于第一检测模块和第二检测模块分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来诊断受试者是否罹患非AD认知障碍。

Description

诊断及鉴别诊断非阿尔兹海默病认知障碍的方法、系统、组合物和试剂盒 技术领域
本申请涉及生物医学技术领域，尤其是涉及体外诊断检测技术领域，涉及采用双标志物和/或多标志物进行非阿尔兹海默病认知障碍检测的方法和系统，优选采用双标志物和/或多标志物同时进行非阿尔兹海默病认知障碍检测的方法和系统。
背景技术
阿尔兹海默病(Alzheimer’s Disease,AD)主要由β淀粉样蛋白沉积及神经缠结导致中枢神经系统神经元损伤，患者出现认知障碍症状。临床工作中患者出现认知障碍症状就诊，认知障碍症状并非只由AD一种原因引起，临床工作中诊断患者为AD时其中常混杂有非AD认知障碍，其误诊率为23～88％，非AD认知障碍包括Lewy体痴呆、额颞叶痴呆、Pick病、伴有痴呆的肌萎缩性侧索硬化症等多种疾病。
基于临床认知量表及症状的诊断很难将AD与非AD认知障碍进行区分，影像学检查费用极为高昂然而对于鉴别AD与非AD认知障碍作用有限，AD与非AD认知障碍鉴别在临床工作中及科研领域一直是难点及研究瓶颈，并且为患者诊疗就医及后续治疗造成极大障碍，影响其治疗效果。本申请提供的诊断及鉴别诊断非AD认知障碍方法，能够有效提高AD与非AD认知障碍鉴别诊断能力，辅助非AD认知障碍诊断，能够极大改善非AD认知障碍误诊率。
基于脑脊液的生物标志物检测在神经系统疾病研究中广泛应用，但是在临床应用中由于脑脊液采集的有创性很难被患者接受，极大地限制了临床转化与后续应用。本申请主要基于外周血检测对非AD认知障碍进行诊断，能够广泛应用于临床实践及大规模筛查。同时，本申请中关键生物标志为创新性发现的外周血神经来源细胞外囊泡(Extracellular Vesicle,EV)相关生物标志物，能够通过检测外周血中神经系统来源EV及其携带的疾病相关蛋白直 接反应中枢神经系统病变，从而实现对非AD认知障碍的诊断及鉴别诊断。本申请核心检测技术为纳米流式检测技术，通过这一技术实现对外周血中神经系统来源EV高灵敏、高通量检测，并且能够实现快速、低成本检测，为临床应用及大规模筛查提供了技术支持。
本申请聚焦非AD认知障碍诊断及鉴别诊断这一临床及科研难题，通过全新纳米流式检测技术，应用创新发现的中神经系统来源EV标志物，实现非AD认知障碍快速、高效诊断及鉴别诊断，为临床非AD认知障碍诊断工作提供新的技术手段及方法。
发明内容
如上所述，在本领域中还未存在利用外周体液有效地对非AD认知障碍进行诊断、鉴别诊断的系统、方法以及试剂盒，本申请旨在提供一种能够在外周体液中有效识别到不同中枢神经系统来源生物标志物，将其与疾病相关标志物联合检测，多重标记同时检测，以达到避免获取脑脊液，只通过少量外周体液样本就可以反应中枢神经系统变化的效果。
即，本申请利用在外周体液中识别中枢神经系统来源的生物标志物进行非AD认知障碍诊断及鉴别诊断。
具体来说，本申请涉及以下内容：
1.一种用于诊断及鉴别诊断非AD认知障碍的系统，其包括：
第一检测模块，其用于检测受试者体液中EV的中枢神经系统来源生物标志物，以确认携带中枢神经系统来源特异性标志物的EV的数量和粒径；
第二检测模块，其用于检测受试者体液中EV的非AD认知障碍相关的标志物以确认携带非AD认知障碍相关的标志物的EV的数量和粒径；
诊断模块，其基于第一检测模块和第二检测模块分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来诊断受试者是否罹患非AD认知障碍。
2.根据项1所述的系统，其中，
所述第一检测模块和所述第二检测模块同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关的标志物；或者
所述第一检测模块和所述第二检测模块为同一模块，其同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关生物标志物。
3.根据项1或2所述的系统，其还包括：
富集模块，其用于获取受试者的体液并对其进行预处理以富集体液中的EV。
4.根据项3所述的系统，其中，所述富集模块还包括用于对富集的EV进行筛选。
5.根据项1-4中任一项所述的系统，其中，
诊断模块统计同时检测到携带中枢神经系统来源生物标志物和非AD认知障碍相关的生物标志物的EV的数量，基于统计的同时检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物的EV的数量占总EV的数量的比值来诊断受试者是否罹患非AD认知障碍。
6.根据项1-5中任一项所述的系统，其中，所述粒径为相关蛋白阳性EV分布数量最多处所对应的粒径，诊断模块基于检测的粒径来鉴别诊断出罹患认知障碍的受试者罹患非AD认知障碍而不是阿尔兹海默病的受试者。
7.根据项1-6中任一项所述的系统，其中，所述EV为神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
8.根据项1-7中任一项所述的系统，其中，所述体液选自血液、血清、血浆、唾液、尿液、淋巴液、精液或乳汁中的一种或两种以上。
9.根据项1-8中任一项所述的系统，其中，所述中枢神经系统来源标志物为G蛋白偶联受体162(G Protein-Coupled Receptor 162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
10.根据项1-9中任一项所述的系统，其中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
11.根据项3所述的系统，其中，所述富集模块具有进行以下步骤中的一种或两种以上的子模块：离心、超速离心、超滤管过滤、聚合沉降、特异 性抗体捕获。
12.根据项1-11中任一项所述的系统，其中第一检测模块用于使受试者的EV与经标记的、与中枢神经系统来源标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有中枢神经系统来源生物标志物的EV的存在及含量。
13.根据项1-12中任一项所述的系统，其中，第二检测模块用于使受试者的EV与经标记的、与非AD认知障碍相关标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有非AD认知障碍相关标志物的EV的存在及含量。
14.根据项12或13所述的系统，其中，所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
15.一种用于诊断及鉴别诊断非AD认知障碍的组合物，其包括：
用于靶向中枢神经系统来源标志物的抗体，以及
用于靶向非AD认知障碍相关的标志物的抗体。
16.根据项15所述的组合物，其中，所述中枢神经系统来源标志物为G蛋白偶联受体162(G Protein-Coupled Receptor 162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
17.根据项15或16所述的组合物，其中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
18.根据项15-17中任一项所述的组合物，其中，所述用于靶向中枢神经系统来源标志物的抗体和所述用于靶向非AD认知障碍相关的标志物的抗体是经标记的抗体，优选所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
19.一种用于检测受试者非AD认知障碍的试剂盒，其包括：
用于检测受试者生物体液中EV的中枢神经系统来源标志物的试剂，以及
用于检测受试者生物体液中EV的非AD认知障碍相关的标志物的试剂。
20.根据项19所述的试剂盒，其中，所述用于检测受试者生物体液中EV的中枢神经系统来源标志物的试剂和用于检测受试者生物体液中EV的非AD认知障碍相关的标志物的试剂为项15-18中任一项所述的组合物。
21.根据项19所述的试剂盒，还包括：
用于获取受试者的生物样本的试剂和装置，优选用于获取受试者EV的试剂和装置。
22.一种用于诊断及鉴别诊断非AD认知障碍的方法，其包括：
第一检测步骤，其检测受试者体液中EV的中枢神经系统来源生物标志物，以确认携带中枢神经系统来源特异性标志物的EV的数量和粒径；
第二检测步骤，其检测受试者体液中EV的非AD认知障碍相关的标志物以确认携带非AD认知障碍相关的标志物的EV的数量和粒径；
诊断步骤，其基于第一检测步骤和第二检测步骤分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来诊断受试者是否罹患非AD认知障碍。
23.根据项22所述的方法，其中，
所述第一检测步骤和所述第二检测步骤同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关的标志物；或者
所述第一检测步骤和所述第二检测步骤为同一步骤，其同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关生物标志物。
24.根据项22或23所述的方法，其还包括：
富集步骤，其获取受试者的体液并对其进行预处理以富集体液中的EV。
25.根据项24所述的方法，其中，所述富集步骤还包括对富集的EV进行筛选。
26.根据项22-25中任一项所述的方法，其中，
诊断步骤统计同时检测到携带中枢神经系统来源生物标志物和非AD认知障碍相关的生物标志物的EV的数量，基于统计的同时检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物的EV的数量占总EV的 数量的比值来诊断受试者是否罹患非AD认知障碍。
27.根据项22-26中任一项所述的方法，其中，所述粒径为相关蛋白阳性EV分布最多处对应的粒径，诊断步骤基于检测的粒径来鉴别诊断出罹患认知障碍的受试者罹患非AD认知障碍而不是AD。
28.根据项22-27中任一项所述的方法，其中，所述EV为神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
29.根据项22-28中任一项所述的方法，其中，所述体液选自血液、血清、血浆、唾液、尿液、淋巴液、精液或乳汁中的一种或两种以上。
30.根据项22-29中任一项所述的方法，其中，所述中枢神经方法来源标志物为G蛋白偶联受体162(G Protein-Coupled Receptor 162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
31.根据项22-30中任一项所述的方法，其中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
32.根据项25所述的方法，其中，所述富集步骤具有进行以下步骤中的一种或两种以上的子步骤：离心、超速离心、超滤管过滤、聚合沉降、特异性抗体捕获。
33.根据项22-32中任一项所述的方法，其中第一检测步骤使受试者的EV与经标记的、与中枢神经系统来源标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有中枢神经系统来源生物标志物的EV的存在及含量。
34.根据项22-33中任一项所述的方法，其中，第二检测步骤使受试者的EV与经标记的、与非AD认知障碍相关标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有非AD认知障碍相关标志物的EV的存在及含量。
35.根据项33或34所述的方法，其中，所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记 或胶体金标记。
发明的效果
利用本申请的方法、系统、试剂盒以及组合物，即使仅仅利用受试者的外周体液也能够诊断及鉴别受试者是否罹患AD，并能够将罹患AD和非AD认知障碍进行鉴别诊断。
利用本申请的方法、系统、试剂盒以及组合物能够有效地从外周体液中富集且特异性地标记能够反映非AD认知障碍疾病变化的生物标志物，相比直接检测外周体液中的疾病相关标志物，诊断效果更优。
利用本申请的方法、系统、试剂盒以及组合物可以有效地利用外周体液来进行检测，从而可以避免创伤性地获取受试者的脑脊液，大大降低受试者的取样风险、大大减轻检测的困难程度、大大增加检测的临床应用性和推广性。
利用本申请的方法、系统、试剂盒以及组合物，能够同时检测中枢神经系统来源标志物与疾病相关标志物，降低样本检测时间，更加高效、便捷。
本申请的核心是采用双标志物和/或多标志物进行非AD认知障碍检测的方法和系统，可以实现双标志物和/或多标志物的同时检测，即利用标志物来确认EV中来源于中枢神经系统的部分，在此基础上利用与疾病相关的标志物，产生的共同检测结果为疾病的诊断、鉴别诊断、追踪和药物评估服务。
附图说明
图1A显示对单颗粒纳米流式细胞仪使用250nm荧光质控球的质控结果；
图1B显示对单颗粒纳米流式细胞仪使用68～155nm粒径质控球的质控结果；
图1C显示对超速离心获得的EV的粒径分布、浓度分析结果；
图2A显示实施例4的发现队列中，与NC组和NAD组相比，AD组血浆中GPR162蛋白阳性EV占总EV数量的比值有下降的趋势，但这种差异无统计学显著性；
图2B显示实施例4的发现队列中，与NC组相比，AD组血浆中pTau217 蛋白阳性EV占总EV数量的比值显著降低(****,p<0.0001)；与NC组相比，NAD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(***,p<0.001)；
图2C显示实施例4的发现队列中，血浆中GPR162蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(***,p<0.001)均存在显著性差异；
图2D显示实施例4的发现队列中，通过受试者工作特征曲线(Receiver operating characteristic curve,ROC)分析进行诊断效率评估，GPR162蛋白和pTau217蛋白双标的曲线下面积(Area under curve,AUC)为0.85(NC VS AD)；
图2E显示实施例4的发现队列中，与NC组和NAD组相比，AD组血浆中GABRD蛋白阳性EV占总EV数量的比值有下降的趋势，但这种差异无统计学显著性；
图2F显示实施例4的发现队列中，与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(*,p<0.01)；
图2G显示实施例4的发现队列中，血浆中GABRD蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(***,p<0.001)均存在显著性差异；
图2H显示实施例4的发现队列中，通过ROC分析进行诊断效率评估，GABRD蛋白和pTau217蛋白双标的AUC为0.85(NC VS AD)；
图2I显示实施例4的发现队列中，使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217数据，AUC为0.91(NC VS AD)；
图3A显示实施例4的发现队列中，与NAD组相比，AD组血浆中GPR162蛋白和pTau217蛋白双阳性EV分布极值对应的粒径显著降低(***,p<0.001)；
图3B显示实施例4的发现队列中，AD组血浆中GABRD蛋白和pTau217蛋白双阳性EV分布极值对应的粒径也显著降低(**,p<0.01)；
图3C显示实施例4的发现队列中，使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217分布极值粒径数据，AUC为0.82(AD VS NAD)；
图4A显示实施例4的验证队列中，与NC组和NAD组相比，AD组血浆中GPR162蛋白阳性EV占总EV数量的比值有下降的趋势，但这种差异无统计学显著性；
图4B显示实施例4的验证队列中，与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(****,p<0.0001)；与NAD组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(****,p<0.0001)；
图4C显示实施例4的验证队列中，血浆中GPR162蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、AD组VS NAD组(****,p<0.0001)均存在显著性差异；
图4D显示实施例4的验证队列中，通过ROC分析进行诊断效率评估，GPR162蛋白和pTau217蛋白双标的AUC为0.74(NC VS AD)；
图4E显示实施例4的验证队列中，与NC组相比，AD组血浆中GABRD蛋白阳性EV占总EV数量的比值显著下降(***,p<0.001)；与NC组相比，NAD组血浆中GABRD蛋白阳性EV占总EV数量的比值也显著下降(****,p<0.0001)；此外，与AD组相比，NAD组血浆中GABRD蛋白阳性EV占总EV数量的比值显著下降(****,p<0.0001)；
图4F显示实施例4的验证队列中，与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(***,p<0.001)；NAD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(***,p<0.001)；
图4G显示实施例4的验证队列中，血浆中GABRD蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(****,p<0.0001)、AD组VS NAD组(*,p<0.01)均存在显著性差异；
图4H显示实施例4的验证队列中，通过ROC分析进行诊断效率评估，GABRD蛋白和pTau217蛋白双标AUC为0.84(NC VS AD)；
图4I显示实施例4的验证队列中，使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217数据，AUC为0.93(NC VS AD)。
图5A显示实施例4的验证队列中，与NAD组相比，AD组血浆中GPR162蛋白和pTau217蛋白双阳性EV分布极值对应的粒径显著降低(***, p<0.001)；
图5B显示实施例4的验证队列中，AD组血浆中GABRD蛋白和pTau217蛋白双阳性EV分布极值对应的粒径也显著降低(**,p<0.01)；
图5C显示实施例4的验证队列中，使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217分布极值粒径数据，AUC为0.88(AD VS NAD)；
图6A显示实施例7中，与NC组和NAD组相比，AD组血浆中CHAT蛋白阳性EV占总EV数量的比值显著降低(**,p<0.01)；
图6B显示实施例7中，与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(****,p<0.001)；与NC组相比，NAD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(***,p<0.01)；
图6C显示实施例7中，血浆中CHAT蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.001)、NC组VS NAD组(***,p<0.05)均存在显著性差异；
图6D显示实施例7中，通过ROC分析进行诊断效率评估，CHAT蛋白和pTau217蛋白双标的AUC为0.88(NC VS AD)；
图6E显示实施例7中，通过ROC分析进行诊断效率评估，CHAT蛋白和pTau217蛋白双标的AUC为0.88(AD VS NAD)；
图6F显示实施例7中，与NC组相比，AD组血浆中NR2D蛋白阳性EV占总EV数量的比例显著降低(***,p<0.001)；与NAD组相比，AD组血浆中NR2D蛋白阳性EV占总EV数量的比例也显著降低(***,p<0.001)；
图6G显示实施例7中，与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(****,p<0.0001)；与NAD组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比例也显著降低(***,p<0.001)；
图6H显示实施例7中，血浆中NR2D蛋白和pTau217蛋白双阳性EV占总EV数量的比例在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(***,p<0.001)均存在显著性差异；
图6I显示实施例7中，通过ROC分析进行诊断效率评估，NR2D蛋白和pTau217蛋白双标的AUC为0.82(NC VS AD)；
图6J显示实施例7的发现队列中，通过ROC分析进行诊断效率评估，NR2D蛋白和pTau217蛋白双标的AUC为0.69(AD VS NAD)；
图6K显示实施例7中，使用逻辑回归分析Enter方法纳入CHAT+pTau217和NR2D+pTau217数据，AUC＝0.96(NC VS AD)；
图6L显示实施例7中，使用逻辑回归分析Enter方法纳入CHAT+pTau217和NR2D+pTau217数据，AUC＝0.88(AD VS NAD)。
具体实施方式
下面将参照附图更详细地描述本申请的具体实施例。虽然附图中显示了本申请的具体实施例，然而应当理解，可以以各种形式实现本申请而不应被这里阐述的实施例所限制。相反，提供这些实施例是为了能够更透彻地理解本申请，并且能够将本申请的范围完整的传达给本领域的技术人员。
需要说明的是，在说明书及权利要求当中使用了某些词汇来指称特定组件。本领域技术人员应可以理解，技术人员可能会用不同名词来称呼同一个组件。本说明书及权利要求并不以名词的差异来作为区分组件的方式，而是以组件在功能上的差异来作为区分的准则。如在通篇说明书及权利要求当中所提及的“包含”或“包括”为一开放式用语，故应解释成“包含但不限定于”。说明书后续描述为实施本申请的较佳实施方式，然所述描述乃以说明书的一般原则为目的，并非用以限定本申请的范围。本申请的保护范围当视所附权利要求所界定者为准。
在本申请中细胞外囊泡(Extracellular Vesicles,EV)是细胞间通信的成熟介质，是由不同类型的激活或凋亡细胞释放的小膜囊泡，包括白细胞、血小板、红细胞和内皮细胞，在人类和动物体液中均可检测到。EV被分为三个主要群体:凋亡小体、微泡和外泌体。
在本申请的一个具体实施方式中，本申请涉及一种诊断及鉴别诊断非阿尔兹海默病认知障碍，即“非AD认知障碍”的方法、系统、组合物和试剂盒，其包括：检测受试者生物体液中EV的中枢神经系统来源标志物，检测受试者生物体液中EV的非AD认知障碍相关的标志物，以及基于中枢神经 系统来源标志物和非AD认知障碍相关的标志物的检测结果来鉴别诊断受试者是否罹患非AD认知障碍。
在本申请的一个具体实施方式中，本申请涉及一种诊断及鉴别诊断非阿尔兹海默病认知障碍，即“非AD认知障碍”的方法、系统、组合物和试剂盒，其包括：检测受试者生物体液中EV的中枢神经系统来源标志物以确认具有中枢神经系统来源标志物的EV的数量和粒径，检测受试者生物体液中EV携带的非AD认知障碍相关的标志物以确认具有非AD认知障碍相关的标志物的EV的数量和粒径，以及基于中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来鉴别诊断受试者是否罹患非AD认知障碍，其中，检测受试者生物体液中的中枢神经系统来源标志物和检测受试者生物体液中的非AD认知障碍相关的标志物同时进行。
在本申请的一个具体实施方式中，本申请涉及一种诊断及鉴别诊断非阿尔兹海默病认知障碍，即“非AD认知障碍”的方法、系统、组合物和试剂盒，其包括：第一检测模块，其用于检测受试者体液中EV携带的中枢神经系统来源标志物以确认携带中枢神经系统来源标志物的EV的数量和粒径，第二检测模块，其用于检测受试者体液中EV携带的非AD认知障碍相关的标志物以确认具有非AD认知障碍相关的标志物的EV的数量和粒径，以及诊断模块，其基于第一检测模块和第二检测模块分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来鉴别诊断受试者是否罹患非AD认知障碍。
在本申请的一个具体实施方式中，本申请涉及一种诊断及鉴别诊断非阿尔兹海默病认知障碍，即“非AD认知障碍”的方法、系统、组合物和试剂盒，其包括：第一检测模块，其用于检测受试者体液中EV携带的中枢神经系统来源标志物以确认携带中枢神经系统来源标志物的EV的数量和粒径，第二检测模块，其用于检测受试者体液中EV携带的非AD认知障碍相关的标志物以确认携带非AD认知障碍相关的标志物的EV的数量和粒径，以及诊断模块，其基于第一检测模块和第二检测模块分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来鉴别诊断受试者是否罹患非AD认知障碍。所述第一检测模块和所述第二检测模块同时检测受试者生物体液中的中枢神经系统来源标志物和检测受试者生物体液中的 非AD认知障碍相关的标志物；或者所述第一检测模块和所述第二检测模块为同一模块，其同时检测受试者生物体液中的中枢神经系统来源标志物和检测受试者生物体液中的非AD认知障碍相关的标志物。
如上所述，在本申请的方法和系统中，发明人独创性地开发出一种新的方法和系统，即采用具有不同作用的双标志物和/或多标志物来进行检测，尤其是可以同时通过这样的双标志物和/或多标志物来进行检测，从而仅仅利用少量外周体液也能够有效地诊断及鉴别诊断非AD认知障碍。这样的检测方法和系统不需要提取患者的脑脊液，大大减轻了患者的取样风险。同时由于采用具有标识中枢系统来源的标志物和与待检测疾病相关的标志物的双重标记和/或多重标记，可以大大提高检测的准确程度，如果进一步同时进行检测，还可以提高整体检测的效率。而现有的其它方法往往需要更为复杂的提取、富集、或纯化步骤等才能够获取用于诊断的EV。本申请则简化了操作步骤，独创性地利用来源于中枢神经系统的标志物来标注来源，并结合与疾病相关的标志物，从而实现了疾病检测准确度和效率的提升。
进一步地，本申请的方法还包括：获取受试者的生物体液并对其进行预处理以富集生物体液中的EV，检测受试者生物体液中的中枢神经系统来源标志物是指检测受试者体液中富集的EV中的中枢神经系统来源标志物，检测受试者生物体液中的非AD认知障碍相关的标志物是指检测受试者体液中富集的EV携带的非AD认知障碍相关的标志物。
进一步地，本申请的方法还包括：获取受试者的生物体液并对其进行预处理以富集生物体液中的EV，对富集的EV进行筛选，检测受试者生物体液中的中枢神经系统来源标志物是指检测受试者体液中筛选的EV中的中枢神经系统来源标志物，检测受试者生物体液中的非AD认知障碍相关的标志物是指检测受试者体液中筛选的EV携带的非AD认知障碍相关的标志物。
本申请的方法还包括诊断模块统计同时检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物的EV的数量，基于统计的同时检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物的EV的数量占总EV的数量的比值来鉴别诊断受试者是否罹患非AD认知障碍。
在本申请的一个具体的实施方式中，同时检测到携带中枢神经系统来源标志物和认知障碍相关的标志物的EV的数量占总EV生物样本的数量的比 值，在健康受试者和认知障碍(AD和非AD)受试者中存在显著差异。例如与健康受试者相比，该比值在AD和非AD受试者中显著降低。
进一步地，诊断模块基于检测的粒径来区分罹患认知障碍的受试者罹患阿尔兹海默病或罹患非AD认知障碍，其中所述粒径为分布极值对应的粒径。具体来说，通常将检测到中枢神经系统来源标志物和AD相关的标志物两者的EV称为双阳性EV，基于双阳性EV的数量和粒径来区分罹患认知障碍的受试者罹患AD或罹患非AD认知障碍。在本申请中，分布极值对应的粒径是指颗粒分布数量最多的粒径大小。在一个具体的实施方式中，分布极值对应的粒径是通过纳米流式检测仪及相关纳米颗粒流式分析仪测量得到的。
在本申请中，通过中枢神经系统来源标志物和非AD相关的标志物的EV的数量占总EV的数量的比值即可判断受试者是否罹患认知障碍。但是将认知障碍中的阿尔兹海默病和非AD认知障碍区分则需要进一步基于所检测到的EV的中枢神经系统来源标志物和EV的非AD认知障碍相关的标志物的分布极值对应的粒径。
在本申请的一个具体的实施方式中，同时检测到携带中枢神经系统来源标志物和认知障碍相关的标志物的分布极值对应的粒径，在AD和非AD认知障碍受试者中存在显著差异。例如与非AD受试者相比，该粒径在AD受试者中显著降低。
进一步地，本申请的系统还包括：富集模块，其对获取受试者的生物体液进行预处理以富集生物体液中的EV。
所述富集模块还可以包括用于对富集的EV进行筛选，以进一步提高所得到的EV的准确度。
本申请还涉及一种用于检测非AD认知障碍的组合物，其包括：用于靶向中枢神经系统来源标志物的抗体，以及用于靶向非AD认知障碍相关的标志物的抗体。
本申请还涉及一种用于检测受试者非AD认知障碍的试剂盒，其包括：用于检测受试者生物体液中EV的中枢神经系统来源标志物的试剂，以及用于检测受试者生物体液中EV的非AD认知障碍相关的标志物的试剂。
在一个具体的实施方式中，用于检测受试者生物体液中的中枢神经系统来源标志物的试剂和用于检测受试者生物体液中的非AD认知障碍相关的标 志物的试剂为本申请所描述的上述组合物。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，生物体液为血液、血清、血浆、唾液、尿液、淋巴液、精液或乳汁。优选的生物体液是血液、血清、血浆、唾液或尿液。用于获取受试者生物体液的方法可以是任何本领域技术人员已知的方法。本领域技术人员可以针对所选用的生物体液的方法来从受试者中获取。
如在本文中所涉及的细胞外囊泡(Extracellular Vesicle，EV)是指从细胞膜上脱落或者从细胞分泌的双层膜结构的囊泡状小体，直径从40nm到1000nm不等。EV主要由微囊泡(Microvesicles，MVs)和外泌体(Exosomes，Exs)组成，微囊泡是细胞激活、损伤或凋亡后从细胞膜脱落的小囊泡，直径约为100nm～1000nm。外泌体(Exosomes)由细胞内的多泡小体(Multivesicular Bodies)与细胞膜融合后以外泌体的形式释放到细胞外，直径约为30～150nm，可以由众多不同类型的细胞所释放，并且执行不同的细胞功能，包括细胞间通讯、抗原呈递、和蛋白质以及核酸的转移。EV广泛存在于细胞培养上清以及各种体液(血液、淋巴液、唾液、尿液、精液、乳汁)中，携带有细胞来源相关的多种蛋白质、脂类、DNA、mRNA、miRNA等，参与细胞间通讯、细胞迁移、血管新生和免疫调节等过程。在一个具体的实施方式中，优选所述EV为神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，获取受试者的生物体液并对其进行预处理以富集生物体液中的EV的方法可以为离心、超速离心、超滤管过滤、聚合沉降或特异性抗体捕获。在本文中，离心、超速离心、超滤管过滤、聚合沉降或特异性抗体捕获均具有本领域技术人员可以理解的含义，本领域技术人员可以根据待获取的EV来选择合适的方法。
在本申请的方法或系统的一个实施方式中，采用超速离心的方法来从生物体液中富集EV，尤其是富集神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
在本申请的方法或系统的一个实施方式中，采用普通离心或超滤管过滤来富集EV，尤其是富集神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
在本申请的方法或系统的一个实施方式中，采用脂质探针对富集EV，尤其是富集神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV进行筛选。在本申请的方法或系统的一个实施方式中，脂质探针的序列为TTTTTTTTTTTTTTTTTTTTTTTTTTTTTT(SEQ ID NO:1)；5'端修饰：5`6-CY3；3'端修饰：3`Cholesteryl。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源标志物是来源于如下神经元或细胞的生物标志物：成熟神经元、少突胶质细胞、星形胶质细胞、小胶质细胞、未成熟神经元、施旺细胞、放射状胶质细胞、中间前体细胞、谷氨酸能神经元、GABA能神经元、多巴胺能神经元、5-羟色胺能神经元、胆碱能神经元。在本申请的方法或系统或组合物或试剂盒的具体实施方式中，优选中枢神经系统来源标志物是神经元来源的生物标志物。在本申请的方法或系统或组合物或试剂盒的具体实施方式中，优选中枢神经系统来源标志物是星形胶质细胞和/或少突胶质细胞来源的生物标志物。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源标志物为位于中枢神经系统来源的EV表面的标志物。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为G蛋白偶联受体162(G Protein-Coupled Receptor162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为G蛋白偶联受体162(G Protein-Coupled Receptor162,GPR162)。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为G蛋白偶联受体162(G Protein-Coupled Receptor162,GPR162)和γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)和谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为GPR162蛋白，所述非AD认知障碍相关的标志物为pTau217蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为GABRD蛋白，所述非AD认知障碍相关的标志物为pTau217蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为GPR162蛋白和GABRD蛋白，所述非AD认知障碍相关的标志物为pTau217蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为CHAT蛋白，所述非AD认知障碍相关的标志物为pTau217蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为NR2D蛋白，所述非AD认知障碍相关的标志物为 pTau217蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述中枢神经系统来源的标志物为CHAT蛋白和NR2D蛋白，所述非AD认知障碍相关的标志物为pTau217蛋白。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，检测受试者生物体液中的中枢神经系统来源标志物的步
骤包括：使受试者的EV与经标记的、与中枢神经系统来源标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断携带中枢神经系统来源标志物的EV的存在及含量；所述非AD认知障碍相关的标志物为蛋白质，检测受试者生物体液中的非AD认知障碍相关的标志物的步骤包括：使受试者的EV与经标记的、与非AD认知障碍相关标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断携带非AD认知障碍相关标志物的EV的存在及含量。
进一步，在具体的实施方式中，优选时受试者的EV同时与经标记的、与中枢神经系统来源标志物特异性反应的抗体和经标记的、与非AD认知障碍相关标志物特异性反应的抗体进行反应，从而高效地追踪到双标和/或多标阳性的EV。
进一步，在本申请的方法或系统或组合物或试剂盒的具体实施方式中，还包括统计检测到中枢神经系统来源标志物和非AD认知障碍相关的标志物两者的EV的数量，和测量检测到中枢神经系统来源标志物和非AD认知障碍相关的标志物两者的EV的粒径，这样可以在追踪到双标和/或多标阳性的EV之后，还可以充分地考虑这样的EV的数量和/或其粒径，结合这些指标的结果来分析受试者罹患非AD认知障碍的风险。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，荧光标记物选自以下中的一种或两种以上：Qdot525、Qdot545、Qdot565、Qdot585、Qdot605、Qdot625、Qdot655、Qdot705、Qdot800、Alexa350、Alexa 405、Alexa488、Alexa 532、Alexa546、Alexa555、Alexa 568、Alexa 594、Alexa647、 Alexa700、Alexa750。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记均可以采用本领域技术人员所熟知的方法。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，检测反应后标记信号的强度以判断中枢神经系统来源标志物的存在及含量可以采用，例如免疫测定，如ELISA、Luminex、MSD、Quanterix、Singulex、eCL8000、Cobas是用于测量蛋白质生物标志物的优选方法。
在本申请的方法或系统或组合物或试剂盒的具体实施方式中，用于统计检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物两者的EV的数量，和/或测量检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物两者的EV的粒径的检测仪器，包括但不限于粒度分析仪、纳米流式细胞仪。例如，利用纳米颗粒追踪技术检测EV的粒径，以及利用纳米流式分析技术检测上述双阳性的EV的数量。
在本申请的一个具体的实施方式中，涉及一种用于检测非AD认知障碍的组合物，其包括：用于靶向中枢神经系统来源标志物的抗体，以及用于靶向非AD认知障碍相关的标志物的抗体。
在本申请的一个具体的实施方式中，所述用于靶向中枢神经系统来源标志物的抗体和所述用于靶向非AD认知障碍相关的标志物的抗体是经标记的抗体，优选所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
在本申请的一个具体的实施方式中，一种用于检测非AD认知障碍的组合物，其包括：用于靶向GPR162蛋白的抗体，以及用于靶向tau(pTau217)蛋白的抗体。
在本申请的一个具体的实施方式中，一种用于检测非AD认知障碍的组合物，其包括：用于靶向GABRD蛋白的抗体，以及用于靶向tau(pTau217)蛋白的抗体。
本申请涉及一种用于检测受试者非AD认知障碍的试剂盒，其包括：用于检测受试者生物体液中的中枢神经系统来源标志物的试剂，以及用于检测受试者生物体液中EV的非AD认知障碍相关的标志物的试剂。所述用于检 测受试者生物体液中EV的中枢神经系统来源标志物的试剂和用于检测受试者生物体液中的非AD认知障碍相关的标志物的试剂可以为上述本申请涉及的组合物。
在本申请涉及的试剂盒中，还包括用于获取受试者的EV的试剂和装置。其中，用于获取EV的试剂和装置可以包括本领域技术人员所知的常用的试剂盒和装置。
利用本申请的方法、系统、试剂盒以及组合物，即使仅仅利用受试者的少量外周体液就能够诊断受试者是否罹患非AD认知障碍进行诊断及鉴别。
利用本申请的方法、系统、试剂盒以及组合物能够有效地从外周体液中富集且特异性地标记能够反映非AD认知障碍变化的生物标志物，相比直接检测外周体液中的疾病相关标志物，诊断效果更优。
利用本申请的方法、系统、试剂盒以及组合物可以有效地利用外周体液来进行检测，从而可以避免创伤性地获取受试者的脑脊液，大大降低受试者的取样风险、大大减轻检测的困难程度、大大增加检测的临床应用性和推广性。利用本申请的方法、系统、试剂盒以及组合物，能够同时检测中枢神经系统来源标志物与疾病相关标志物，降低样本检测时间，更加高效、便捷。
实施例
实施例1
超速离心对EV进行富集
1.来自受试者的血浆在37℃迅速解冻(2min内)，涡旋混匀；
2.血浆样品(>300μL)在4℃，2,000×g条件下离心15min，取上清；
3.接着在4℃，12,000×g条件下离心30min，取上清；
4.吸取100μL离心后的血浆至1.5mL超离管中，并加入900μL 0.22μm过滤的磷酸盐缓冲液(PBS)(pH7.4)，混匀；
5.在4℃，100,000×g条件下，超速离心70min；
6.弃去约900μL上清，向剩余液体中(约100μL)加入200μL PBS(0.22μm滤膜过滤)，使用200μL量程移液器吹吸200次，重悬沉淀；
7.向重悬后的液体中加入700μL PBS(0.22μm滤膜过滤)，混匀；
8.在4℃，100,000×g条件下，超速离心70min；
9.弃去上清，保留约150μL液体，使用200μL量程移液器吹吸200次，重悬沉淀；
10.分装，保存至-80℃待用。
实施例2
对超速离心获得的EV进行表征
使用Nanofcm对超速离心获得的EV的粒径及浓度进行表征。
1.首先使用250nm荧光质控球、68～155nm粒径质控球(购自厦门福流生物科技有限公司)对Nanofcm进行调试，使其荧光检测、粒径区分处于最佳状态(图1A、1B)。其中，图1A显示单颗粒纳米流式细胞仪使用250nm荧光质控球的质控结果。散射光通道(SS)，绿色荧光通道(FITC)和红色荧光通道(PC5)均处于信号值较高(第1列)、信号峰均一(第2，3列)的状态；说明单颗粒纳米流式细胞仪对荧光信号的检测已调整至较好的状态。图1B显示单颗粒纳米流式细胞仪使用68～155nm粒径质控球的质控结果。粒径质控球是由4种粒径不同的球混合而成，如图1B所示，单颗粒纳米流式细胞仪能够精确检测到该粒径球中4种不同粒径群的颗粒；说明该仪器对粒径信号的检测已调整至较好的状态。
2.取超离获得的细EV，根据具体情况，将其稀释至仪器记录颗粒数4000-8000个/min为佳。
3.根据Nanofcm记录结果，对超离获得的细EV的粒径分布、浓度情况进行分析(图1C)。
实施例3
利用标记方法标记用于检测生物标志物的抗体
使用的试剂：
利用Alexa Fluro荧光标记kit，来标记中枢神经系统来源EV生物标志物的抗体和相关阿尔茨海默病生物标志物的抗体。其中，中枢神经系统来源EV生物标志物的抗体为GPR162和GABRD多克隆抗体。阿尔茨海默病生物标志物的抗体为pTau217多克隆抗体。其中，标记GPR162和GABRD多克隆抗体的试剂为ZenonTM Alexa FluorTM 488Rabbit IgG Labeling Kit，购买 自Thermo Fisher Scientific；标记pTau217多克隆抗体的试剂为ZenonTM Alexa FluorTM 647 Rabbit IgG Labeling Kit，购买自Thermo Fisher Scientific。
1.样本封闭
(1)取10μL利用上述方法经超速离心分离的EV至0.6mL离心管；
(2)加入10μL 2％BSA溶液(0.22μm滤膜过滤)，混匀；
(3)室温(25-26℃)封闭1小时，以去除非特异性结合；
(4)加入10μL PBS(0.22μm滤膜过滤)稀释，终止封闭。
2.样本标记
本实验涉及中枢神经系统特异性标志物GPR162和GABRD；疾病相关标志物抗体pTau217。使用ZenonTM Alexa FluorTM 488 Rabbit IgG Labeling Kit标记GPR162和GABRD，ZenonTM Alexa FluorTM 647 Rabbit IgG Labeling Kit标记pTau217；
(1)取1μg相应标志物的抗体，用PBS(0.22μm滤膜过滤)稀释至5μL(0.2μg/μL)；
(2)加入5μL ZenonTM Alexa FluorTM Labeling Kit A液，混匀后室温(25-26℃)避光孵育20min；
(3)向(2)步骤的溶液中加入3μL(3μg)ZenonTM Alexa FluorTM Labeling Kit B液(B液稀释至1μg/μL)，混匀后室温(25℃)避光孵育10min，以淬灭游离荧光；
(4)加入PBS(0.22μm滤膜过滤)稀释至总体积50μL；
(5)取5μL ZenonTM Alexa FluorTM 647 Rabbit IgG Labeling Kit标记的pTau217于步骤1封闭完毕的样本中，混匀后室温(25-26℃)避光孵育5min；
(6)加入3μL ZenonTM Alexa FluorTM 488 Rabbit IgG Labeling Kit标记的GPR162或GABRD于步骤(5)样本中，混匀后4℃避光孵育过夜；
3.样本固定
(1)次日，在标记完毕的样本中加入20μL 4％PFA(0.22μm滤膜过滤)，混匀后室温(25-26℃)避光孵育20min；
(2)加入50μL PBS(0.22μm滤膜过滤)稀释固定后的样本，待用。
4.检测
使用NanoFCM纳米流式分析仪进行检测标记信号强度与粒径分布，从 而确定相关生物标志物的存在及含量。
实施例4
在大量临床样本中检测上述生物标记物的鉴别诊断能力
1.发现队列
分别获取年龄、性别匹配的健康对照(NC组)28例、阿尔茨海默病受试者(AD组)44例、非AD-认知障碍(NAD组)31例的血浆样本，作为发现队列，利用上述实施例3方法进行实验。
利用纳米流式分析仪NanoFCM分别检测GPR162、GABRD单荧光标记、pTau217单荧光标记、GPR162和pTau217双荧光标记的EV数量、以及GABRD和pTau217双荧光标记的EV数量，计算其占总EV数量的比值，检测其区分NC、AD、NAD的能力。
发现队列中，与NC组和NAD组相比，AD组血浆中GPR162蛋白阳性EV占总EV数量的比值有下降的趋势，但这种差异无统计学显著性(图2A)；与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(****,p<0.0001)；与NC组相比，NAD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(***,p<0.001)(图2B)；血浆中GPR162蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(***,p<0.001)均存在显著性差异(图2C)。通过受试者工作特征曲线(receiver operating characteristic curve,ROC)分析进行诊断效率评估，GPR162蛋白和pTau217蛋白双标的曲线下面积(area under curve,AUC)为0.85(图2D)。
发现队列中，与NC组和NAD组相比，AD组血浆中GABRD蛋白阳性EV占总EV数量的比值有下降的趋势，但这种差异无统计学显著性(图2E)；与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(*,p<0.01)(图2F)；血浆中GABRD蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(***,p<0.001)均存在显著性差异(图2G)。通过ROC分析进行诊断效率评估，GABRD蛋白和pTau217蛋白双标的曲线下面积(area under curve,AUC)为0.85(图2H)。
使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217数据，AUC为0.91(NC VS AD)(图2I)。
经分析，依靠GPR162+pTau217或者GABRD+pTau217双阳性EV占总EV数量的比值，虽然能够很好地区分NC和AD患者；但是对AD和NAD的鉴别诊断能力有限。因此，将粒径分布作为参考因素，探索出使用极值粒径来对AD和NAD进行区分；即：不同实验组样本，目标蛋白阳性的囊泡的粒径分布可能存在差异；我们将目标蛋白阳性囊泡数目最大值对应的粒径进行分析，结果如下：
发现队列中，与NAD组相比，AD组血浆中GPR162蛋白和pTau217蛋白双阳性EV分布极值对应的粒径显著降低(***,p<0.001)(图3A)；AD组血浆中GABRD蛋白和pTau217蛋白双阳性EV分布极值对应的粒径也显著降低(**,p<0.01)(图3B)；使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217分布极值粒径数据，AUC为0.82(AD VS NAD)(图3C)。
发现队列的结果显示，血浆中GPR162蛋白和pTau217蛋白双阳性EV占总EV数量的比值以及血浆中GABRD蛋白和pTau217蛋白双阳性EV占总EV数量的比值均具有较好的区分健康对照和阿尔茨海默病的潜力，尤其是采用GPR162+pTau217双阳性EV比例与GABRD+pTau217双阳性EV比例进行联合诊断。对GPR162+pTau217双阳性EV和GABRD+pTau217双阳性EV分布极值粒径进行联合分析，能够较好地鉴别诊断阿尔茨海默病与非AD-痴呆。
紧接着，在样本量更大的验证队列中进行验证。
2.验证队列
分别获取年龄、性别匹配的健康对照(NC组)57例、阿尔茨海默病受试者(AD组)88例、非AD-痴呆(NAD组)62例的血浆样本，作为验证队列，利用上述实施例3方法进行实验。
验证队列中，与NC组和NAD组相比，AD组血浆中GPR162蛋白阳性EV占总EV数量的比值有下降的趋势，但这种差异无统计学显著性(图4A)；与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显 著降低(****,p<0.0001)；与NAD组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(****,p<0.0001)(图4B)；血浆中GPR162蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、AD组VS NAD组(****,p<0.0001)均存在显著性差异(图4C)。通过受试者工作特征曲线(receiver operating characteristic curve,ROC)分析进行诊断效率评估，GPR162蛋白和pTau217蛋白双标的曲线下面积(area under curve,AUC)为0.74(NC VS AD)(图4D)。
验证队列中，与NC组相比，AD组血浆中GABRD蛋白阳性EV占总EV数量的比值显著下降(***,p<0.001)；与NC组相比，NAD组血浆中GABRD蛋白阳性EV占总EV数量的比值也显著下降(****,p<0.0001)；此外，与AD组相比，NAD组血浆中GABRD蛋白阳性EV占总EV数量的比值显著下降(****,p<0.0001)(图4E)；与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(***,p<0.001)；NAD组血浆中pTau217蛋白阳性EV占总EV数量的比值也显著降低(***,p<0.001)(图4F)；血浆中GABRD蛋白和pTau217蛋白双阳性EV占总EV数量的比值在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(****,p<0.0001)、AD组VS NAD组(*,p<0.01)均存在显著性差异(图4G)。通过ROC分析进行诊断效率评估，GABRD蛋白和pTau217蛋白双标的曲线下面积(area under curve,AUC)为0.84(图4H)。
使用逻辑回归分析Enter方法纳入GPR162+pTau217和GABRD+pTau217数据，AUC为0.93(NC VS AD)(图4I)。
与发现队列情况相似，依靠GPR162+pTau217或GABRD+pTau217双阳性EV占总EV数量的比值，虽然能够很好地区分NC和AD患者；但是对AD和NAD的鉴别诊断能力有限。因此，我们依旧将粒径分布作为参考因素，使用极值粒径来对AD和NAD进行区分；我们将目标蛋白阳性囊泡数目最大值对应的粒径进行分析，结果如下：
验证队列中，与NAD组相比，AD组血浆中GPR162蛋白和pTau217蛋白双阳性EV分布极值对应的粒径显著降低(***,p<0.001)(图5A)；AD组血浆中GABRD蛋白和pTau217蛋白双阳性EV分布极值对应的粒径也显著降低(**,p<0.01)(图5B)；使用逻辑回归分析Enter方法纳入 GPR162+pTau217和GABRD+pTau217分布极值粒径数据，AUC为0.88(AD VS NAD)(图5C)。
验证队列的结果与发现队列一致，即：血浆中GPR162蛋白和pTau217蛋白双阳性EV占总EV数量的比值以及血浆中GABRD蛋白和pTau217蛋白双阳性EV占总EV数量的比值均具有较好的区分健康对照和阿尔茨海默病的潜力，尤其是采用GPR162+pTau217双阳性EV比例与GABRD+pTau217双阳性EV比例进行联合诊断。对GPR162+pTau217双阳性EV和GABRD+pTau217双阳性EV分布极值粒径进行联合分析，能够较好地鉴别诊断阿尔茨海默病与非AD-痴呆。
综上，实施例4结果表明，采用GPR162+pTau217双阳性EV比例与GABRD+pTau217双阳性EV比例进行联合分析，能够较好地区分健康对照和阿尔茨海默病。对GPR162+pTau217双阳性EV和GABRD+pTau217双阳性EV分布极值粒径进行联合分析，能够较好地鉴别诊断阿尔茨海默病与非AD-痴呆。
实施例5
用PEG8000沉降富集EV
1.来自受试者的血浆在37℃迅速解冻(2min内)，涡旋混匀；
2.血浆样品(>300μL)在4℃，2,000×g条件下离心15min，取上清；
3.接着在4℃，12,000×g条件下离心30min，取上清；
4.吸取10μL离心后的血浆至1.5mL离心管中，加入70μL PBS和20μL 40％PEG8000，充分吹打混匀，室温静置30min；
5.12000g，4℃，离心20min；
6.弃上清，加入100μL PBS重悬，吹打混匀，10μL/管进行分装，保存于-80℃备用。
实施例6
1.样本封闭
(1)取10μL利用上述方法经PEG8000的EV至0.6mL离心管；
(2)加入10μL 2％BSA溶液(0.22μm滤膜过滤)，混匀；
(3)室温(25-26℃)封闭1小时，以去除非特异性结合；
(4)加入10μL PBS(0.22μm滤膜过滤)稀释，终止封闭。
2.样本标记
利用标记方法标记用于检测生物标志物的抗体
使用的试剂：
利用Alexa Fluro荧光标记kit，来标记CHAT、NR2D，以及pTau217的抗体。其中，标记CHAT抗体的试剂为ZenonTM Alexa FluorTM 488 Mouse IgG2b Labeling Kit，购买自Thermo Fisher Scientific；标记NR2D抗体的试剂为ZenonTM Alexa FluorTM 488Rabbit IgG Labeling Kit，购买自Thermo Fisher Scientific；标记pTau217抗体的试剂为ZenonTM Alexa FluorTM 647 Rabbit IgG Labeling Kit，购买自Thermo Fisher Scientific。
(1)取1μg相应标志物的抗体，用PBS(0.22μm滤膜过滤)稀释至5μL(0.2μg/μL)；
(2)加入5μL ZenonTM Alexa FluorTM Labeling Kit A液，混匀后在室温(25-26℃)避光孵育20min；
(3)向(2)步骤的溶液中加入3μL(3μg)ZenonTM Alexa FluorTM Labeling Kit B液(B液稀释至1μg/μL)，混匀后室温(25℃)避光孵育10min，以淬灭未结合的游离荧光素；
(4)加入PBS(0.22μm滤膜过滤)稀释至总体积50μL；
(5)取5μL ZenonTM Alexa FluorTM 647 Rabbit IgG Labeling Kit标记的pTau217于步骤1封闭完毕的样本中，混匀后室温(25-26℃)避光孵育5min；
(6)加入3μL ZenonTM Alexa FluorTM 488Rabbit IgG Labeling Kit标记的CHAT或NR2D于步骤(5)样本中，混匀后4℃避光孵育过夜；
3.探针孵育
使用试剂：合成DNA anchor，其序列为TTTTTTTTTTTTTTTTTTTTTTTTTTTTTT(SEQ ID NO:1)；5'端修饰：5`6-CY3；3'端修饰：3`Cholesteryl。该脂质探针能够与EV膜结合，探针标记阳性的颗粒被认为是真正的EV；该方法进一步提高了EV标记的科学性和准确度。
(1)次日，加入62μL PBS+5μL脂质探针(脂质探针工作液浓度10 μM)(反应体积100ul，探针终浓度500nM)，4℃避光孵育1h。
(2)在标记完毕的样本中加入100μL 4％PFA(0.22μm滤膜过滤)，混匀后室温(25-26℃)避光孵育20min；
(3)用PBS稀释到合适浓度上机，标准：用CytoFLEX检测，每秒颗粒数小于1万个颗粒。在脂质探针门下收集50000个颗粒(此情况下总颗粒数约为100000；换言之，使用脂质探针对实施例5得到颗粒进行筛选，其中真正的EV约为50％)。
4.检测
使用CytoFLEX的VSSC模式检测脂质探针阳性情况下，相关蛋白标记的阳性比例。
实施例7
在临床样本中检测上述生物标记物的鉴别诊断能力
分别获取年龄、性别匹配的健康对照(NC组)20例、阿尔茨海默病受试者(AD组)20例、非AD-痴呆(NAD组)20例的血浆样本，利用上述实施例6的方法进行实验。
利用CytoFLEX的VSSC模式分别检测CHAT、NR2D单荧光标记、pTau217单荧光标记、CHAT和pTau217双荧光标记的EV数量、以及NR2D和pTau217双荧光标记的EV数量，计算其占脂质探针标记阳性的EV数量的比例，检测其区分NC、AD、NAD的能力。
结果显示，与NC组相比，AD组血浆中CHAT蛋白阳性EV占总EV数量的比例显著降低(***,p<0.001)；与NAD组相比，AD组血浆中CHAT蛋白阳性EV占总EV数量的比例也显著降低(**,p<0.01)(图6A)。与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比例显著降低(***,p<0.001)；与NAD组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比例也显著降低(**,p<0.01)(图6B)；血浆中CHAT蛋白和pTau217蛋白双阳性EV占总EV数量的比例在NC组VS AD组(***,p<0.001)、AD组VS NAD组(*,p<0.05)均存在显著性差异(图6C)。通过ROC分析进行诊断效率评估，CHAT蛋白和pTau217蛋白双标的AUC分别为0.88(NC VS AD)(图6D)，AUC＝0.82(AD vs NAD)(图6E)。
此外，与NC组相比，AD组血浆中NR2D蛋白阳性EV占总EV数量的比例显著降低(***,p<0.001)；与NAD组相比，AD组血浆中NR2D蛋白阳性EV占总EV数量的比例也显著降低(***,p<0.001)(图6F)。与NC组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比值显著降低(****,p<0.0001)；与NAD组相比，AD组血浆中pTau217蛋白阳性EV占总EV数量的比例也显著降低(***,p<0.001)(图6G)；血浆中NR2D蛋白和pTau217蛋白双阳性EV占总EV数量的比例在NC组VS AD组(****,p<0.0001)、NC组VS NAD组(***,p<0.001)均存在显著性差异(图6H)。通过ROC分析进行诊断效率评估，NR2D蛋白和pTau217蛋白双标的AUC分别为0.82(NC VS AD)(图6I)，0.69(AD vs NAD)(图6J)。
使用逻辑回归分析Enter方法纳入CHAT+pTau217和NR2D+pTau217数据，AUC＝0.96(NC VS AD)(图6K)；AUC＝0.88(AD VS NAD)(图6L)。
经分析，依靠CHAT+pTau217和NR2D+pTau217双阳性EV占总EV数量的比例，不仅能够很好地区分NC和AD患者；也能有效鉴别诊断AD和NAD。
以上所述，仅是本申请的较佳实施例而已，并非是对本申请作其它形式的限制，任何熟悉本专业的技术人员可能利用上述揭示的技术内容加以变更或改型为等同变化的等效实施例。但是凡是未脱离本申请技术方案内容，依据本申请的技术实质对以上实施例所作的任何简单修改、等同变化与改型，仍属于本申请技术方案的保护范围。

Claims (35)

  1. 一种用于诊断及鉴别诊断非阿尔兹海默病(Alzheimer’s Disease,AD)认知障碍的系统，其包括：
    第一检测模块，其用于检测受试者体液中细胞外囊泡(Extracellular Vesicle,EV)的中枢神经系统来源生物标志物，以确认携带中枢神经系统来源特异性标志物的EV的数量和粒径；
    第二检测模块，其用于检测受试者体液中EV的非AD认知障碍相关的标志物以确认携带非AD认知障碍相关的标志物的EV的数量和粒径；
    诊断模块，其基于第一检测模块和第二检测模块分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来诊断受试者是否罹患非AD认知障碍。
  2. 根据权利要求1所述的系统，其中，
    所述第一检测模块和所述第二检测模块同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关的标志物；或者
    所述第一检测模块和所述第二检测模块为同一模块，其同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关生物标志物。
  3. 根据权利要求1或2所述的系统，其还包括：
    富集模块，其用于获取受试者的体液并对其进行预处理以富集体液中的EV。
  4. 根据权利要求3所述的系统，其中，所述富集模块还包括用于对富集的EV进行筛选。
  5. 根据权利要求1-4中任一项所述的系统，其中，
    诊断模块统计同时检测到携带中枢神经系统来源生物标志物和非AD认知障碍相关的生物标志物的EV的数量，基于统计的同时检测到携带中枢神经系统来源标志物和非AD认知障碍相关的标志物的EV的数量占总EV的数量的比值来诊断受试者是否罹患非AD认知障碍。
  6. 根据权利要求1-5中任一项所述的系统，其中，所述粒径为相关蛋白阳性EV分布数量最多处所对应的粒径，诊断模块基于检测的粒径来鉴别诊 断出罹患认知障碍的受试者罹患非AD认知障碍而不是AD。
  7. 根据权利要求1-6中任一项所述的系统，其中，所述EV为神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
  8. 根据权利要求1-7中任一项所述的系统，其中，所述体液选自血液、血清、血浆、唾液、尿液、淋巴液、精液或乳汁中的一种或两种以上。
  9. 根据权利要求1-8中任一项所述的系统，其中，所述中枢神经系统来源标志物为G蛋白偶联受体162(G Protein-Coupled Receptor 162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
  10. 根据权利要求1-9中任一项所述的系统，其中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
  11. 根据权利要求3所述的系统，其中，所述富集模块具有进行以下步骤中的一种或两种以上的子模块：离心、超速离心、超滤管过滤、聚合沉降、特异性抗体捕获。
  12. 根据权利要求1-11中任一项所述的系统，其中第一检测模块用于使受试者的EV与经标记的、与中枢神经系统来源标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有中枢神经系统来源生物标志物的EV的存在及含量。
  13. 根据权利要求1-12中任一项所述的系统，其中，第二检测模块用于使受试者的EV与经标记的、与非AD认知障碍相关标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有非AD认知障碍相关标志物的EV的存在及含量。
  14. 根据权利要求12或13所述的系统，其中，所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
  15. 一种用于诊断及鉴别诊断非AD认知障碍的组合物，其包括：
    用于靶向中枢神经系统来源标志物的抗体，以及
    用于靶向非AD认知障碍相关的标志物的抗体。
  16. 根据权利要求15所述的组合物，其中，所述中枢神经系统来源标志物为G蛋白偶联受体162(G Protein-Coupled Receptor 162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
  17. 根据权利要求15或16所述的组合物，其中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
  18. 根据权利要求15-17中任一项所述的组合物，其中，所述用于靶向中枢神经系统来源标志物的抗体和所述用于靶向非AD认知障碍相关的标志物的抗体是经标记的抗体，优选所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
  19. 一种用于检测受试者非AD认知障碍的试剂盒，其包括：
    用于检测受试者生物体液中EV的中枢神经系统来源标志物的试剂，以及
    用于检测受试者生物体液中EV的非AD认知障碍相关的标志物的试剂。
  20. 根据权利要求19所述的试剂盒，其中，所述用于检测受试者生物体液中EV的中枢神经系统来源标志物的试剂和用于检测受试者生物体液中EV的非AD认知障碍相关的标志物的试剂为权利要求15-18中任一项所述的组合物。
  21. 根据权利要求19所述的试剂盒，还包括：
    用于获取受试者的生物样本的试剂和装置，优选用于获取受试者EV的试剂和装置。
  22. 一种用于诊断及鉴别诊断非AD认知障碍的方法，其包括：
    第一检测步骤，其检测受试者体液中EV携带的中枢神经系统来源生物标志物，以确认携带中枢神经系统来源特异性标志物的EV的数量和粒径；
    第二检测步骤，其检测受试者体液中EV的非AD认知障碍相关的标志物以确认携带非AD认知障碍相关的标志物的EV的数量和粒径；
    诊断步骤，其基于第一检测步骤和第二检测步骤分别获得的中枢神经系统来源标志物和非AD认知障碍相关的标志物的检测结果来诊断受试者是否 罹患非AD认知障碍。
  23. 根据权利要求22所述的方法，其中，
    所述第一检测步骤和所述第二检测步骤同时检测受试者体液中的中枢神经方法来源标志物和检测受试者体液中的非AD认知障碍相关的标志物；或者
    所述第一检测步骤和所述第二检测步骤为同一步骤，其同时检测受试者体液中的中枢神经系统来源标志物和检测受试者体液中的非AD认知障碍相关生物标志物。
  24. 根据权利要求22或23所述的方法，其还包括：
    富集步骤，其获取受试者的体液并对其进行预处理以富集体液中的EV。
  25. 根据权利要求24所述的方法，其中，所述富集步骤还包括对富集的EV进行筛选。
  26. 根据权利要求22-25中任一项所述的方法，其中，
    诊断步骤统计同时检测到携带中枢神经方法来源生物标志物和非AD认知障碍相关的生物标志物的EV的数量，基于统计的同时检测到携带中枢神经方法来源标志物和非AD认知障碍相关的标志物的EV的数量占总EV的数量的比值来诊断受试者是否罹患非AD认知障碍。
  27. 根据权利要求22-26中任一项所述的方法，其中，所述粒径为相关蛋白阳性EV分布数量最多处所对应的粒径，诊断步骤基于检测的粒径来鉴别诊断出罹患认知障碍的受试者罹患非AD认知障碍而不是AD。
  28. 根据权利要求22-27中任一项所述的方法，其中，所述EV为神经元来源的EV、星形胶质细胞来源的EV、少突胶质细胞来源的EV或小胶质细胞来源的EV。
  29. 根据权利要求22-28中任一项所述的方法，其中，所述体液选自血液、血清、血浆、唾液、尿液、淋巴液、精液或乳汁中的一种或两种以上。
  30. 根据权利要求22-29中任一项所述的方法，其中，所述中枢神经系统来源标志物为G蛋白偶联受体162(G Protein-Coupled Receptor 162,GPR162)、γ-氨基丁酸A型受体亚基δ(Gamma-Aminobutyric Acid Type A Receptor Subunit Delta,GABRD)、乙酰胆碱转移酶(Choline O-acetyltransferase，CHAT)、谷氨酸离子型受体NMDA型亚基2D(Glutamate  ionotropic receptor NMDA type subunit 2D，NR2D)中的一种或两种以上。
  31. 根据权利要求22-30中任一项所述的方法，其中，所述非AD认知障碍相关的标志物为第217位磷酸化tau(pTau217)蛋白。
  32. 根据权利要求25所述的方法，其中，所述富集步骤具有进行以下步骤中的一种或两种以上的子步骤：离心、超速离心、超滤管过滤、聚合沉降、特异性抗体捕获。
  33. 根据权利要求22-32中任一项所述的方法，其中第一检测步骤使受试者的EV与经标记的、与中枢神经系统来源标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有中枢神经方法来源生物标志物的EV的存在及含量。
  34. 根据权利要求22-33中任一项所述的方法，其中，第二检测步骤使受试者的EV与经标记的、与非AD认知障碍相关标志物特异性反应的抗体进行反应，以及检测反应后标记信号的强度以判断具有非AD认知障碍相关标志物的EV的存在及含量。
  35. 根据权利要求33或34所述的方法，其中，所述标记选自以下中的一种或两种以上：荧光标记、同位素标记、酶标记、化学发光剂标记、量子点标记或胶体金标记。
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